Team Projects for Competition 2018

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Project Team Location Challenges Entered Datasets Used meta
Academic Connect I'm Learnding Sunshine Coast (USC) 7 4 This project aimed to address the lack of collaboration between government, universities and industry to encourage innovation. We started by looking over various data set’s and settled on using the govhack 2018 IP data combined with OECD innovation data. We took the IP data, sorted by year of application removed duplicate names, and reorganised it by the number of IP applications. Looking at the data 1200 companies in australia had registered Patents in the last 10 years. These are the companies that it is recommended to target and contact first to build the community as they are the most likely to use this platform. For the website development, data was scraped from publicly available university webpages to find their available areas of research. OECD information was also used to ensure that this was a valid issue for Australia.
👟 Active Cities 👟 🚶‍♀️ Active Aces 🚶‍♂️ Darwin 8 5 Active Cities aims at encouraging people to exercise, socialise and to discover their local city. It provides the user with information regarding a variety of activity types, from going for a walk in a nearby park to exploring a local museum - catering for a variety of personal preferences. Active Cities uses mutiple datasources including Bureau of Meteorology, Darwin City OpenData Parks and Playgrounds in order to provide a customized experience for the individual.
Age-Friendly Canberra Project 77 Canberra 8 4 Please view our Github page for a comprehensive project profile: https://github.com/ma-al/gh18-p77 - The Age-Friendly Planning Tool maps government data on population projections for the Canberra region and assists users in identifying areas requiring increased support and development, now and into the future. The intended users of our tool are town planners, government and private enterprises - and potentially older Canberrans. Our tool maps data from the Australian Institute of Health and Welfare on ageing population predictions and data from the Department of Health on current aged care services in Canberra to help understand what areas may require age-friendly resources and infrastructure. It also combines ACT Government data on bus stop locations to identify where additional stops may be needed to support older residents who rely on public transport. The age-friendly planning tool presents a front-end visualisation that is available on desktop and mobile. It relies on an analytics back-end for data processing and stores data up in the cloud. This architecture enables flexibility and mobility on the part of the user and allows the system to scale for higher performance. The intention of our project is to demonstrate how a range of government data can be combined to predict and support the needs of older Canberrans. In addition to the datasets we have used, additional government data such as data on footpaths, pedestrian crashes, hospitals and health care facilities could be included to better identify all areas of development to prepare for aging populations. Our mapping tool could be expanded on a larger geographic scale to encourage a whole-of-government collaborative approach across Australia. According to the Australian Bureau of Statistics (ABS) 2016 Census, the Australian population is ageing, with the proportion of people over 65 steadily increasing over the last century. As we age, our housing, transport and social needs change. Areas with more older residents may require additional resources that are often only identified after residents experience hardship. We spoke to Lucy who volunteers at Villaggio Sant' Antonio’s, a local aged care facility, who told us that the footpaths in the area are too narrow and residents can’t walk side by side or use their mobility scooters. Many parks and community spaces in the area also have poor wheelchair accessibility. This discourages residents from exercising and socialising with friends outdoors. Our tool can help plan for these issues in advance. Our tool will help town planners, government and private enterprises plan how to make Canberra more inclusive for older Canberrans. The tool combines population projections with health services and infrastructure data to identify areas requiring increased support and development, now and into the future. Our tool maps ageing population predictions data and current aged care services data for Canberra to help understand what areas will require age-friendly resources and infrastructure. It also combines local ACT Government data on bus stop locations to identify where additional bus stops may be needed to support older residents. A private business could use the tool to plan the location of its next aged care residence by cross-referencing population projections with location of current facilities. In addition, the ACT government could also use the tool to identify areas where facilities (such as footpaths, bus stops and medical centres) need to be upgraded to better support the changing community. In this way, the tool can help improve the quality of life of residents such as those in St Antonio’s. Over time this concept could be expanded to include a plethora of recreational, health, education services, etc. on a national level to encourage a collaborative approach nationally to support an ageing population, and empower senior residents to make choices based on this information.
AgriInsur AgriInsur Sydney 5 3 The project aims to use environmental and financial data sets to power smart contracts that will radically improve farm insurance making such insurance easier and quicker to obtain. This will contribute the the betterment of the lives and make a social impact on struggling Australian farmers. We used environmental and financial data sets to calculate the insurance fee for a specific amount of cover. The environmental data regarding the precipitation enables a prediction of harvest or natural disaster, which assists the calculation of agricultural insurance.
AiTO SchrodingersHack Gold Coast 5 3 The AiTO is a new and more user friendly way of interacting with people. This is done in two ways, * Firstly via strategically located help centers to allow more people easier access to the service. * Secondly with our Speech analysis retrieval assistant or SARA for short, Sara is designed to be an AI call center assistant to not only solve various caller questions while they are in the queue to speak to a representative but to also display the correct information about the caller if it cannot be solved by SARA alone, this is done in an attempt to drastically reduce wait times and processing speed of the ATO call centers. The following datasets have been used in this project: &nbsp; * ATO/ABS Data -https://data.gov.au/dataset/govhackato/resource/f3bcbd38-b3e9-4a27-8729-2314f05a6ae4 * GNAF - http://gnafld.net/ * Postcode/LatLong - http://www.corra.com.au/australian-postcode-location-data/ &nbsp; ATO TAX CENTER PREDICTION: For a complete breakdown oh how the datasets have been used you can view the Notebook file on the github (https://github.com/giskmov/govhack2018_aito/blob/master/govhack_2018.ipynb) which provides a step by step breakdown of how the data has been used and the prediction model constructed. &nbsp; A brief overview is provided below: 1. Initially the three datasets are cleansed to remove any unnecessary or null values 2. Using primary keys in the datasets these sets are then combined to form a single large table 3. Our label we are trying to predict is the "Count" which is the number of ATO tax help centers per postcode. This label (column) is then removed and placed into a seperate dataset. 4. These two datasets now form our features and labels dataset 5. These datasets are then split and shuffled into training and testing sets for our models 6. A prediction model is then created for use of the data 7. The model is trained on the training set, and validated on the testing set 8. Once the model has reached the required accuracy it is complete and can be used for prediction 9. Based on the data we then predict where the ATO should be placing their help centers 10. A graph is then produced which shows where these centers have been placed &nbsp; As with all ML Applications the results can be improved, tweaking hyperparamters, modifying underlying data, or including additional data can all be done to help achieve a better result. &nbsp; AI POWERED OMNI-CHANNEL CHATBOT: Based on the callers location, we can create a profile based on average income, socio economic index, ethnicity. On their first interaction with Sarah we will also know their gender to a 98% accuracy. &nbsp; This information along with historical caller satisfaction ratings is used to create models that help predict: * Best CSR to send the request to * Optimise the path through the automated system * Predict questions and offer * Measuring customer satisfaction/sentiment &nbsp; Our omni-bot uses natural language processing powered by machine learning to find insights and relationships in text. The service identifies the language of the text; extracts key phrases, places, people, brands, or events; understands how positive or negative the text is; analyzes text using tokenization and parts of speech; and automatically organizes a collection of text files by topic. Using these APIs, you can analyze text and apply the results in a wide range of applications including voice of customer analysis, intelligent document search, and content personalization for web applications. <iframe src="https://onedrive.live.com/embed?cid=019C8CBC4527098E&amp;resid=19C8CBC4527098E%21405&amp;authkey=AO5WBvEZYihRBz8&amp;em=2&amp;wdAr=1.7777777777777777" width="350px" height="221px" frameborder="0">This is an embedded <a target="_blank" href="https://office.com">Microsoft Office</a> presentation, powered by <a target="_blank" href="https://office.com/webapps">Office Online</a>.</iframe> https://1drv.ms/p/s!Ao4JJ0W8jJwBgxX1EQ-KouIP_SY-
Alice Solar Homes SolarAS Alice Springs 7 4 SolarAS has written a website to assist renters and landlords cooperate with the help of real-estate agents to build and maintain high-quality, high-voltage blackout resistant solar systems within their homes. We hope to tap in to the strong enthusiasm and community spirit, business and government goodwill to drive this change and so have also integrated community and social media sites within our page. reference to https://edf.nt.gov.au/developing-sectors/renewable-energy as a basis for chosing solar energy (https://2018.hackerspace.govhack.org/challenges/104), all the links in the challenges https://2018.hackerspace.govhack.org/challenges/54, https://2018.hackerspace.govhack.org/challenges/55 were linked to directly or referenced in building the site.
alitternation alitternation Brisbane 4 3 Littering is an issue that every Australian is aware of, and yet it continues to be a problem despite the millions of dollars spent in clean up costs each year. Alitternation is a web application powered by government data that aims to give Australians both the knowledge and motivation to clean up their communities. With alitternation, users can easily lookup objects via several methods, such as barcode scanning, image recognition and simple product lookups to find out what they can do with it. From there the site can show the user where the nearest receptacle for it is, taking the hassle out of doing the right thing. Alitternation keeps track of all items disposed of, as well as where and when they were found. We hope to provide this data back to the government in order to empower their decision making about litter. With this data, we will be able to learn so much more about where people tend to litter, as well as what products and brands are the worst off. With this, the government will be able to make educated decisions to prevent future littering. To incentivise use of our app, we’re complementing the incoming Container Refund Scheme set to launch in Queensland by giving users the ability to collect 10c when they scan, track and collect eligible litter items. Users who register with alitternation can cash in this credit when the items are handed over to an approved collection point. We've used two main categories of data, data that shows us the current state of littering in QLD (https://data.qld.gov.au/dataset/litter-auditing-data-from-south-west-queensland-litter-prevention-project) and data that provides us with the existing resources to solve this problem (https://data.gov.au/dataset/waste-collection-points + https://www.data.brisbane.qld.gov.au/data/dataset/waste-transfer-stations/resource/60dbf68b-7911-417b-8ae3-056700e681d8)
Anchor Anchor Melbourne 3 8 The aim of this application is to help startups pick the best place to start their new business, or franchises to pick the best place to create a new branch. The app will show an interactive map, which the new business creator can explore, and it’ll give them the information relevant to their new business, such as pedestrian volume, the amount of available parking, and the volume of competitors (or potential business partners) in the area. For example, a person trying to start a cafe might want to find a place with high pedestrian volume or high density of officespace nearby. A tech startup might want to open an office near other tech startups, etc. In short, the app will help startups to find a place to ‘anchor’ their new business. The app combines the data from ANZIC’s business establishments and Pedestrian Volume, and several parking datasets. ANZIC’s data set provides us with the data on the business census within a certain block of Melbourne, providing insight to the opportunities in the area. Since the dataset only covers the city of melbourne, this application will only work in the melbourne city region. However, as we we receive more and more data, the technology can also be used for the whole victoria region, or even all of australia. This application can also be used by the government to help them visualize the state of Melbourne’s industry, e.g. where all the Corporate offices are located, or the level of oversaturation in the city (e.g. which has too many restaurants competing in the same area, and which area could use more restaurants) On top of this, As part of a commercialization strategy, we might even integrate real estate APIs (such as commercialrealestate.com.au), to further easing the process of finding the essential place to start a business.
Anzen Drive Team Drop Table Canberra 3 1 How can technology make us safer on the roads? In ACT since 2000, 13 people have died on average every year due to road based collisions (https://policenews.act.gov.au/crime-statistics-and-data/road-toll). In order to promote awareness around road safety, Team Drop Table has designed a web based application that utilises existing ACT road collision data and a support vector machine algorithm in order to generate the probability of road collisions based on input from users. Traffic accidents are significant cause of injury and loss of life in Australia. Since it is an everyday activity in many Australians lives, it quickly becomes an activity that we don’t associate with risk. Our data aims to create a driving conditions report for users, by allowing users to input their destinations and allowing the application to aggregate risk factors that could apply to their driving route. This currently considers seven variables, such as location, road quality, weather, time of time, lighting conditions and day of the week. This allows the user to benefit from existing data to by being informed more accurately of the risk of their actions, allowing more drivers to be able to pick their driving routs and times with more consideration and allow them to minimise risk taking behaviour such as driving in heavy rain or areas with low quality lighting. There is a need for a program like this, as unlike other states and territories, the ACT boasts few safety applications or programs to promote safety issues amongst drivers. While the ACT Government goes to great effort to ensure the rules and regulations of road engagement are available to road users, there are few campaigns highlighting potential hazards on roads. ACT Policing regularly runs ‘themed’ months that encapsulate certain dangers such as drink driving, speeding, or driver distraction, however more common risk factors such as weather and timing are not often correlated with crash severity or fatalities and promoted in awareness campaigns. ‘Anzen’ comes from the Japanese word for safety – a concept that encompasses the purpose of our 2018 Govhack submission. By giving users information about the chance of an accident we want to increase awareness of road dangers. Having the ability to identify risk allows the driver to focus on potential dangers on the road and should result in fewer accidents. This program mainly derives its risk association from ACT road crash data between 2012-2018. We utilise a SVM (Service Vector Machine) to be able to take this information and separate it into a level of risk based on historical patterns. This data then undergoes controlled Machine Learning to generate a hyper dimensional model that tries to predict the most likely crash to occur. A website front-end was created to collect a small amount of data from the user and see where it lines up into the model. The program does this by; 1. Utilising existing data (the 54,000 entries) on conditions during crashes (time, lighting, road quality, etc.) to train a computer to produce a hyper dimensional model. 2. Comparing theoretical conditions generated by user input to the model created. 3. Providing feedback to the human where there driving conditions fall into the model (likelihood of minor property damage, human injury or even fatality). The good thing about this approach is that it is very easy to incorporate additional variables into the machine. It’s highly scalable and the more relevant variables we are able to add the more accurate the machines predictions become.
A+ Search Datacake Sydney 10 1 We absolutely love the Open Data movement. We are strong believers that we can collectively as a group make the right choices for our society and change positively the life of every citizen. Even tough an incredible amount of data are publicly available it is still quite hard to find the right dataset in the right format with the relevant documentation. We want to improve this situation and help to get closer to a simple and frictionless searching experience. This will accelerate innovative innovations and drive better decisions based on data We analysed the current version of search.gov.au and identify the key issues we want to solve in order to improve user experience. We focused on implementing new features such as: - autocomplete to suggest best keywords based on the initial inputs from the user - dynamic results to provide relevant documents while the user is still typing his/her request - single page application to help the user to focus on his/her query and get all the information he/she needs in one go - mock-up of chatbot functionality to provide personalised assistance to the user
A story of cables and cars Dazed and Confused Sunshine Coast (USC) 7 6 My Bruce Highway anti-congestion scheme - this is a data story of cables and cars. My idea is to use the new undersea internet cable and government support to get most of the cars off the Bruce Highway. I call it "Build it and they will come". My data shows that Bruce highway congestion can be broken into two main categories. My scheme has two steps. Step 1 gives the constructions workers local jobs so we get them off the highway now. Then step 2 mean the Brisbane workers can now work locally using the internet to connect to their employer so they wont need to travel anymore either. Then we can work to create new jobs so that kids like me can get a local job once we finish school. I worked out that this will prevent 65,000 tons of carbon emissions, reduce car costs by $246 million, give employees back 6.3million hours of time or allow them to earn an extra $250 million. And, of course, travelling south will become a lot easier.
A Taxing Problem Nostradata Canberra 3 5 Our focus was the challenge of identifying where the ATO should locate their Tax Help Centers. This project also addressed the challenge of combining data sets and using open data to help governments answer questions. We set out to demonstrate in this challenge how Machine Learning can be used to help government agencies make decisions, in this case where to put Tax Help Centers to best serve the community. We utilised this opportunity to merge data from a variety of sources, namely: 1. ATO individual tax return data from 2014 - 2015 & 2015 - 2016 2. ABS demographic summary data from 2015 & 2016 3. Tax Help Center locations 4. ABS Geography publications Given that the current distribution of Tax Help Centers is not necessarily optimal, the merged data was used to calculate an adjusted score for each postcode's requirement for tax assistance based upon the ATO eligibility criteria. The adjusted scores were used to train a deep neural network to predict the required number of Tax Help Centers in a postcode, which after using cross-folds validation to verify the accuracy of the model, achieved a score of **96%**
atofeedback atofeedback Adelaide 2 3 The idea is to create a profile of people and offer suggestions to better serve the customer. This is designed as an internal tool to be used by the call centre as well as client facing support workers to help answer questions. As the system is used the system will start to learn and be better able to surface information that will be useful. This tool is designed to be an internal tool used by staff to better handle calls and in person requests for more information. As the basic information is collected the system will build up a profile of that user to surface questions and answers that are likely to be relevant to you.
ATO Tax Help Centres FutureSight Canberra 1 0 A Machine learning based model to determine the most appropriate location of tax centres across Austalia Data sets included the ATO dataset provided as well as the Australian Post code information provided by Australian Post. The premise of the analysis is that clients of tax service have an income threshold and there are multiple factors that can estimate the income threshold. The existing dataset is analysed in R to determine the critical factors affecting income threshold and a forecast for 2021 is applied to determine the threshold. A geo-spatial map of the postcode and the thresholds is used to graphically analysis the impact of the factors on the location of the tax centres.
Aug Data My City Gold Coast 3 6 This project is visualize underground assets using Augmented Reality. At present the underground assets can only be seen on map. With this application using Augmented reality and also using City of Gold Coast open data sets Sewer Connection, Recycled Water Pipe, Potable water pipe, raw water main, Drainage pipe, Fiber optic cable etc, we can visualize the actual assets at the location. Application camera takes the current location and shows any underground assets underneath using Augmented Reality. City of Gold Coast has many underground assets like water pipes, drainage pipes etc and these assets can be seen on the map using GIS co-ordinates. Using this open data, the project is trying to visualize the underground assets such that user can find exactly where they are located using Augmented Reality. This functionality is very useful for Council staff and also for local public to locate the assets, Dial before dig, Plumbers, NBN connections, Tree planters, Real Estate Industry. By using this applcation, the Construction industry can take dvantage in the tender process by visualising complex 3D architectural models and to give site engineers a tool that will help them plan and manage their site more effectively. In Emergency Management Councils have realised that it is severely important to know where underground assets are before a disaster strikes. It gives the emergency management crew a tool to respond fast based on information that is instantly available and easy to update from ground zero. Usage of Aug Data: 1. Visualize any underground assets at a particular location 2. Easy for Maintenance staff to locate underground assets 3. Reduce time and money for Plumbers to locate the underground pipes for connections 4. Real Estate buyers can look at the underground assets before buying the property 5. Cable connections made easy
Aussie Animal Scavenger Hunt Fellowship Rocketship Milksteak Convoke Brisbane 3 4 <p>Aussie Animal Scavenger Hunt (AASH) is an educational product that will have kids learning an Indigenous language while adventuring outdoors searching for animals.</p> <br /><br /> <p>Scavenger Guides (such as teachers, parents or carers) can use our website to print out Animal Scavenger Hunt Maps for their local area. The Scavenger Guide also has a local Indigenous language dictionary with all the animals they can expect to find.</p> <br /><br /> <p>The scavenger hunt will begin with a language lesson to learn Indigenous animal names. Then, kids can then take their maps out into the field and check off each animal they find as well as writing the traditional Aboriginal name in the blank field provided.</p> <p>We are using the Gold Coast region as a case study to create a prototype product. The indigenous language dictionary has been sourced from the Yugambeh Museum. Fauna sightings and pathways data has been sourced from the Gold Coast City Council.</p> <br /><br /> <p>The Fauna sightings dataset has been transformed by merging in the Yugambeh Indigenous language dictionary. Our new dataset includes both the common and Yugambeh names for each animal.</p> <br><br> <p>Topographic basemaps have been sourced from QSpatial, the Queensland Government open spatial data portal.</p> <br><br> <p>After placing both the Gold Coast pathways and the transformed Gold Coast fauna sightings onto the map we discovered that these two datasets combined could provide further use outside the scavenger hunt. For example, another use we envisioned would be assisting hikers and bike riders in their awareness about what animals they might encounter on their journey .</p>
Baby Namer-er Platypuce Productions Campbelltown 1 2 Program used to efficiently search the most and least popular baby names relevant to each year.
Backpackers App Solid Adelaide 2 1 **The ideal app for all Backpackers!** It has space for all your memories (syncs your pictures you took in the middle of nowhere!), It has space for your identification (e.g; Passports, Drivers License, Proof of Age). It can even show all the locations you have been to! So hurry up and make this concept a real thing!
“Backwards and Forwards”- South Australia Edition Bachmanns and Fulwoods Mount Gambier 6 2 A board game designed to help people interact with the local historical figures with intriguing life facts, all meshed together in a ‘race-to-the-end” type board game. WE have combined the Significant South Australians data set with the South Australian Key Events data sets in a fun and interactive board game format for all ages.
Beat The Heat Crisp4Good Sydney 1 6 Our project Beat The Heat aims to communicate the urban heat challenges for the residents in the Parramatta LGA during summer. Visualising the data to provide meaningful insights, Beat The Heat conveys the correlation between local temperature and energy consumption for sites in Parramatta, and suggests the need to be forward-thinking to ensure adequate energy resources to meet future needs. We visualize this data in the form of an interactive Power BI visualization. Our visualisations convey the amount of power required by air conditioners in the local government area of Parramatta. Using our visualization users can view historical data on energy consumption and temperature data based on the selected time period or location. We used the Parramatta temperature dataset to estimate the energy consumption of running an air conditioner to cool Paramatta households on a hot summers day. Also, we used census data to determine the total energy expenditure by air conditioners per hour for all households in Parramatta. To determine how much power would be required, the energy company could calculate the amount of power used on a day where air conditioners would not be used as much (on a relatively cool day) and then use our data to predict how much power exactly they would need to supply on a sweltering day, thus reducing the risk of a power outage. Future Additions: If we were to develop this product in the future, we would look at data with more specific daily results such as average amount of hours spent running the air conditioner per day rather than per year. This would allow us to cater our results to various parts of the year where temperatures can vary a lot. We would also combine data from the Bureau of Meteorology to expand our predictions to various locations around the country, especially rural areas as they would be unlikely to have air conditioners. Our visualisations predict the amount of power required by air conditioners in the local government area of Parramatta. We used the Parramatta temperature data set to determine how the maximum temperature changed everyday and combined this with the energy cost of running the air conditioner at 35C to calculate the energy cost when running at the maximum temperature per day. We then used the census data to determine how many households there are in each of suburbs where the data was reported from to calculate total energy expenditure by air conditioners per hour for all suburbs. Another dataset that was used showed the amount of hours spent by each household per year either cooling or heating the house. Since the data we received was from January, we only looked at the cooling hours to determine how long a household would spend cooling their house per day. This led to much better energy prediction results. One use case of this data would be to determine how much extra power would need to be inserted into the grid on days where the temperature is very high. To determine how much extra power would be required to be inserted, the energy company could calculate the amount of power used on a day where air conditioners would not be used as much (on a relatively cool day) and then use our data to predict how much power exactly they would need to supply on a hot day. Then they would be able to predict how much more power they would need to inject in the grid on hot days. Another use case would be for power companies to reduce the price per unit of power supplied when it is in demand which would convince more people to leave the air conditioning on for longer. This could potentially lead to better revenues.
Beautiful Infringements Null VRiables Canberra 10 2 <p>Explosions of colour rip through the night sky, emanating from a single source and branching like lightning during a sultry summer storm. The bright flashes lighting up the sky like a...speed camera? </p> <p> As a rule, art is the use of technical ability and imagination to express the beauty and emotional power of subjects, that invoke a powerful reaction in the heart of the beholder. Whereas, speed cameras are the use of technology to test the speeds of Canberran’s and invokes a powerful reaction to the hip pocket of careless drivers. </p> <p> Our mission is to create something that could be considered beautiful from data that is linked to a subject that is perceived to be so ugly and emotionally charged. Like the sight spring blossoms of Floriade, like the sunset over the Brindabella’s. Behold the Beautiful Infringements of Canberra. </p> We don’t claim to be renaissance artists, but, how hard could it be? <p> Using the 2018 Traffic speed camera locations data from the ACT Government, we loaded the infringement notices for all fixed speed cameras across the ACT into a force directed graph for use within a virtual reality or Augmented reality headset. </p><p> A force directed graph allows the use of physics based springs and colliders within Unity3D. The heirarchy then forces the nodes out from the City root node, to each relevant speed camera and finally to all infringements that those cameras issued this year. </p><p> Rather than hack these datasets to argue for or against the use of speed cameras, we have used Virtual Reality to turn the infringement data from something that is often perceived to be ugly, into something....beautiful.</p>
Big Backyard G.E.O. Janes Launceston 5 12 Big Backyard is a map-app that will allow people travelling around Australia to make use of open data to locate information about attractions at ever-changing locations that are not captured by standard platforms like TripAdvisor. Map your route on the app, then select “what’s near me” to see native animals (devils, penguins, platypus), walking tracks, food vans, and street art in the vicinity. The app will tell you how long to get there, and what you will see. But the mobile, ever-moving nature of these attractions mean that you may not be able to locate the best exact location to find the photo-op you are hunting. So, the app allows people to upload pin-drops of their sightings location and photos. This information is overlaid with the data with official sources like government, university and commercial project data. But as a bonus, the app provides an opportunity to capture information that is not ordinarily available with open source data – to capture more of the story – by providing the information crowdsourced from tourists and members of the community back to these original data sources. When out in the field you can use the AR app to see where others have seen the attractions you are hunting for and the data they have collected in the field. Importantly, it also helps preserve natural heritage fauna hotspots so that locals and tourists alike can continue to have access to see our beautiful wildlife and natural attractions for years to come. Commercially; in Tasmania alone there were a total of 1.28 million people visiting the state last year and visitors spent a total of $2.37 billion on accommodation, attractions, tours, transport and other good and services during this period. We forecast conservatively capturing 1% of the market, at $1 per download representing $128,000 turnover per annum with low ongoing overheads. Now apply that commercial turnover to a national landscape, AND with increasing yearly download growth target of 10% downloads within 3 years. Now we’re talking! Big Backyard will appeal to people who: * are looking for a natural eco-tourism discovery experience in Tasmania * are seeking low/no-cost activities to supplement their more expensive holiday experiences * enjoy adventure travelling, and the opportunity to discover natural wildlife experiences * enjoy exploring new places off the beaten track * want to incorporate recreation, bush walking, nature and exercise into their holiday experience * promotes accessible, free exercise opportunities by providing destination activities for groups such as cardio rehabilitation and mental well-being instead of walking around the same familiar suburban block. *This app will motivate users through push notification to propel residents of our community to get outside and explore. * enables children to develop interest in and learn about our environment and for schools to integrate into curriculum. * data uploads will also assist government to understand the habits of visitors to specific areas which may need formal infrastructure like tracks and viewing barriers to better protect them and the environment as visitor numbers grow. This information will be particularly useful in remote areas where ongoing updates may be difficult to source. * will provide information to help preserve our natural heritage through investing in and protecting the most loved and visited places for the benefit of generations to come. What are you waiting for? Download Big Backyard App now! The Big Backyard map-app uses open source data from Penguin colonies, platypus burrows, rapture nest, shark hot spots, walking tracks, biking tracks, urban art walls, waterfalls, fire trails and The List then overlay that with open Esri base maps and routing services. As an additional input we crowdsource similar data about these categories from locals and tourists to create an energy, urgency and excitement around our urban and natural environment. Locals and tourists can find and can then visit unique highlights nearby including native animal (devils, wombats, platypus), walking tracks, food vans and street art!
BinChicken - Making Australia Clean Again I adopted a puppy today but I'm still here hacking Melbourne 3 4 ## The problem: Over time, Australia has seen waste generation increase, but recycling stagnate. This has significant impacts on the environment - and cost of service. The cost per tonne for kerbside waste handling is twice as high for garbage as it is for recyclables.We have also found in our daily lives that well-meaning people are confused by whether or not their rubbish is recyclable. People recycling a non-recyclable items, or vice versa, cost councils thousands. If we can enable AND encourage more people to recycle a larger percentage of their household waste, we can save both money and the environment. ## Solution: That's why we've created BinChicken. Using machine learning, the mobile app informs users of how to recycle their items when they are unsure (see the video for a demonstration in action). It looks to track users' contributions by using data from Sustainability Victoria to calculate the impact from the items they recycle. This is displayed in relatable terms (kilometres in a car, hours watching TV, etc) along with the actual energy and emissions savings. The impact is scored and combined this into a leaderboard. Some healthy competition between neighbouring suburbs can really fuel the community in its journey toward sustainability! In addition we have features for the user to find their closest waste management facility for additional help in recycling items that are not handled through the regular kerbside waste service. ## Vision: We hope to see a future where as much waste as possible is recycled, saving both money and the environment. We hope to see Australia lead the world into a sustainable future. ## Data To Identify the Problem We used the Local Government Annual Waste Service Report to educate ourselves about the state of affairs when it comes to waste management and recycling. It was clear that while total waste increases, the amount recycled doesn't necessarily keep up. This told us there was a problem we wanted to solve. ## Machine Learning Data We found an image dataset that we used to start training our model. It lets us identify the material of an object (to a pretty good success rate) and we can then direct the user as to how to recycle it. In the future, we look to collect more data by letting users submit additional material and use it to further train the model. ## Waste Impact We used the LCA kerbside recycling calculator to get information about the impact of different items. Eg if you recycle 3 soda cans a week, how many kilometres of driving is the CO2 emission savings equivalent to? This lets us present the user with metrics of their impact that they can relate to more than just the kilograms of CO2. ## Nearby Waste Facilities Using the National Waste Management Database we also provide the user with information about nearby facilities where they can take items that are not handled by the kerbside waste service.
BinHunter BinHunters Hobart 3 1 BinHunter is a mobile game that allows users to capture "bin monsters" near their location. The app promotes awareness of bin locations in a fun way, as well as an exciting way to explore the city. The game uses the Hobart Council's bin data to create spawn points of wild "bin monsters" at these locations. If a user is near enough to a spawn location they can "battle" the monster to gain XP or capture it, similar to Pokemon Go. Based on the type of bin at each location different monsters will spawn, with rarer monsters spawning at the more unique council bin types. Each type of monster has unique attack types, damage and health.
BizX - Business Transformed DXC Technology Canberra 4 4 Unlocking the value in open data and using it to drive social and economic value by helping entrepreneurs, start-ups and businesses start, grow, employ and thrive! Access to freely available open data is key to entrepreneurs and small business owners overcoming the frustrations of an ever more competitive market. This issue is particularly close to our hearts as more jobs are outsourced offshore and unemployment rates rise, we want to help people find alternate ways of working and open new pathways for self-employment in the ACT, and across Australia. Our product is based on the below hypotheses: We believe that the process for starting up a business is difficult and full of uncertainties, and a competitor environment combined with a lack of easily-available demographic data results in an uninformed decision-making environment for new and existing business. We believe that for a business to grow and prosper into the future, an entrepreneur needs information regarding the right location to offer their service or sell their product. Informing new and existing business decision-making using open data is key to nurturing a low entry barrier environment for new and existing business. A Mile in Business Shoes – Helping businesses start, grow, employ and thrive. We believe that for a business to grow and prosper into the future, an entrepreneur needs accurate, relevant and easily accessible location data. Re-using and combining G-NAF, ABS business, and ACT population datasets in several ways, we created a product that provides business viability ratings based on location, competitors and demographics, helping entrepreneurs to identify the best areas to start and grow a business. Our users are everyday, ambitious Australians that want the challenges of setting up a business clarified. This platform also allows State and Federal government to re-use the exact same data to support skill migration, identifying missing skills and incentivising preferred suppliers. Users can use BizX to help them identify the ideal location for their business by highlighting gaps in the market in their target areas.
Boast Your Coast A Nice Well Behaved Cheese 🧀 Brisbane 4 6 Boast Your Coast is a campaign, informative website and Business / Community Hub. The intended audience is residents, owners of small local businesses and tourists. The aim of the Boast Your Coast is to help residents and small businesses within the Sunshine Coast by empowering them with information and data surrounding tourism and employment within their region. Small businesses can sign up and register their business, providing a platform and free exposure. Sometimes business owners struggle with setting up an accessible website or simply do not have time while they are in the process of spinning up a new business. The Boast Your Coast business hub ensures that information regarding local businesses and stores is in an easily accessible format. Residents and visitors can browse the listings and access information about sustainability, as well as the importance of supporting small businesses by shopping locally. Additionally, Boast Your Coast emphasises the Council's intentions surrounding sustainability, environmental responsibility and economic growth. The website provides residents with a way of submitting feedback to ensure they feel heard, especially regarding any potential concerns regarding the tourism industry and its impact on the local community. The Boast Your Coast solution endeavours to foster a sense of community and pride within the Sunshine Coast. It will provide a platform for local businesses to gain exposure, for residents to be heard and for tourists to access information about keeping the Sunshine Coast beautiful.&nbsp;&nbsp; ![Boast Your Coast Home Page](https://2018.hackerspace.govhack.org/rails/active_storage/blobs/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaHBBZ3dCIiwiZXhwIjpudWxsLCJwdXIiOiJibG9iX2lkIn19--04779fa45e24e346ac62ea451e7c05e88debdec9/boastyourcoasthighres2.jpg) Datasets used - International visitors by Queensland Tourism region (Queensland Government) [Link] (https://data.qld.gov.au/dataset/internat-visitors-qld-tourism-region) and Census Data 2011 Qld Employment by Industry (Sunshine Coast) [Link] (https://data.sunshinecoast.qld.gov.au/Society/Census-Data-2011-Qld-Employment-by-Industry/grkm-3d2g). We analysed the International Tourists by Queensland Tourism region data and found that only a small percentage of tourists choose to visit the Sunshine Coast, with Brisbane and the Gold Coast holding the majority of the tourism industry share. With the tourism industry forecasted to growth significantly within the next 10 years, we identified that for the Sunshine Coast to grow commercially (while also maintaining its sense of community and beautiful environment) it must better support local businesses. Our solution presents data in an easily readable format for residents and small businesses to communicate the benefits of growing the tourism industry within the Sunshine Coast region.
Boundless connections In time Melbourne 10 16 Our poject aims to bridge communities together and encourage active lifestyles by paring carers/volunteers with aged and disable. there is alot of data on health and wellbeing, our project aims to increase the positive data out there by encouraging the communities to come together and be active. Location, city and state data is used to encourage application users to venture out and explore together.
Bubbles Team TeamTeam Sydney 9 7 Bubbles creates algorithmically generated, data driven narratives to pop the information and empathy bubbles that exist within today’s digital, atomised society by generating interactive, game-ified, empathy creating narratives. Bubbles uses ABS SA2 census data, AIHW health data and ASFA insolvency data to create algorithmic narratives connecting various “information bubbled” demographics. For example, we use the AIHW and ABS data to generate a data-driven story connecting young Australians to old Australians. Our example story starts at the macro view of the issue, informing the example youth user about statistics for their demographic and then informing them about similar statistics for the target older demographic. This is intended to generate empathy around the target demographic.
Bus' A Move Digital Bureaucrats Adelaide 3 3 We propose a Dynamic Metro Engine to help governments make data-driven decisions to improve public transport services for citizens. This engine consumes live public transport feeds of real time bus data, metrocard validations and GTFS network information. It will provide tools which can be used to identify and predict under-utilised or underserved routes. An interface with alternative transport providers such as rideshare apps or minivan services will allow routes with low occupancy to be catered for by share vehicles. Why run a whole bus for a few passengers when you can use a car? This will help improve the utilisation of both buses and shared vehicles. Plus the data should be shared both ways so that highly requested ride-share journeys can be proposed for future public transport routes. With under-used routes replaced, some of these busses could be reallocated to improve the frequency of the high demand routes we identify and provide a dynamic bus timetable. To minimise the impact on bus users, the metro engine will feed into existing public transport interfaces such as the websites, apps and display screens. Users on low-occupancy bus routes will be directed to catch the alternative transport from their regular stop. With Banded Metrocard validation data and Adelaide Metro General Transit Feed information, we built a tool to identify the most and least popular bus routes and visualised them by colour. SIRI Real time data was analysed to calculate the average delay of different routes.
bVocal Object reference not set to an instance of an object. Hobart 6 6 Our application provides a platform for community consultation about public facilities and points of interest. It provides data on existing infrastructure and allows users to create additional observations. bVocal also allows users to engage in Geo-location specific dialogue to promote community and government involvement and solutions. We used local council data to present a visualisation on the location of local council infrastructure. bVocal allows for community input and consultation on these locations as well as the ability to add new questions, comments and hazards to the dataset. bVocal is an evolving dataset that continues to grow with it's community. bVocal helps governments make decisions by providing a mechanism to engage with the community and understand their needs.
Canberra Business Ninja Team 36 Canberra 9 4 Scaling your SMB (Small and Medium-sized Businesses) is hard work. It's difficult to ascertain if a particular business district or the local corner shops is the best place to move to or best place to set up a new store. Understanding your customer where your customers are is one thing, understanding your business needs is another. CanberraBusiness.Ninja offers local councils and governments the ability to analyse the demographics, geography, infrastructure and other economic data of areas within their jurisdiction by comparing the nature of businesses that already exist within their area of interest to similar businesses that sustainably operate in suburbs with a similar nature. In doing this, segments of the economy, industries, or specific businesses that are lacking within a local council's area of interst are immediately flagged. For example, if a suburb of interest contains 2 bakeries per 1000 people, but a similar suburb sustains 5 bakeries per 1000 people, then the fact that the density of bakeries within the area of interest is flagged. This allows governments to understand the deficiencies within their local economy from which they can plan zoning, infrastructure, and education/training to develop their local economy and create employment. However, just because a government knowns which businesses are under-represented with an area, it is very difficult for them to dictate to entrepreneurs what businesses they should open and where those businesses should be located. CanberraBusiness.Ninja addresses this problem by recommending to entrepreneurs and small business owners which places are optimal to locate their businesses; the under-represented businesses within a council area are the same areas that we recommend entrepreneurs to open businesses. The way that our web application recommends locations to entrepreneurs is based on demographic and economic data to find where their business achieves the best market fit and least competition based on their data input into our application. The data a small business owner inputs relates to the nature of their target customers from which our application analyses the demographics of towns and suburbs to find the best fit. Quirkyness is determined by how many public art displays are in a certain general locality (for example Woden as opposed to Phillip) We take a normalised average of age, income and public art displays against each suburb in Canebrra. This is done by taking the min and max then noramlise to output a score between 0 and 1 that determins the colouring for each suburb.
Care Gov (beta) Oakton Canberra 6 8 Care.gov.au supports young carers to meet their responsibilities and build community whilst telling their story to government and service providers. During initial investigations we found we were unable to find quality information about young carers within the ACT. This meant we were required to access information from Department of Social Service, the Australian Bureau of Statistics, National Disability Insurance Scheme and Carers ACT websites in order to build a picture of the people we were interested in. We decided to create a service that would consume what data we did find and help capture and populate the information that was sorely missing. By combining multiple services currently spread across numerous departments we are able to pull together a clear picture about how young carers are actively using services available to them. One such example was there was no information on how young a person may start to care to how long they might care for. By using the average age someone may live to, the age people become parents and the reduction in life span based on certain conditions, we were able to estimate how long carers may be in the role for. By giving people the ability to actively report how they are using certain services, government can see real time information about how and what young carers are accessing based on their individual needs. Information such as how much carers need to contribute personally to care services, where NDIS money is being spent, and how young carers are coping is data that can be invaluable to helping policy decisions. CARE is not only about using what data we could find to tell the story, but aims to highlight the gap in data that is currently available. CARE provides not only a helpful service to carers, but allows high quality real time data to enable government decisions.
Car park unknown. Unlucky Magician Casey 8 7 Car park unknown. aims to use parking sensor data as a springboard to determine in real-time where parking violations are occurring in the Melbourne CBD. It also assists the public by helping drivers to locate a free car park based on the historical data from the last 4 years. We have designed a web application where users can select the day, time of day, sensor and whether they want input or output for the park. If we continued on this project we would want to overlay other maps showing pedestrian and sidewalk infrastructure to show improvements resulting from previous projects and where there is currently still congestion. It also aims to reimagine the interaction between vehicles, bicycles, sidewalks and pedestrian traffic to utilise the roads we have to move people around the city both quicker and safer. We have used the datasets provided by the City of Melbourne that provides the location and vacancy of the car park bay in real time through the use of in-ground sensor systems. It also shows where parking violations are occurring in real time. Finally the historical data provides insight into how the parking bays are being used by the user through time and location. The Melbourne Council are able to use this data to determine where there is congestion, where is not enough car parks and where parking times are inadequate. Through the use of additional overlays on our map, the data would be able to show where there is mobility support for those needed and if these car parks are being used adequately or if improvements need to be made.
Casey's Blood on the Road The Kwelamen Casey 2 3 An attempt to find an amazeballs solution for Casey's Crash problems Data on road deaths shouldn't take away from the grief of loss of life on the roads
Chain IP Team Cabanossi Sydney 10 1 We use smart contracts and the EOSIO Blockchain Virtual Machine platform to create a better way to handle IP Rights data. This is a proof of concept only, as it is unfeasible right now to push smart contracts to the main EOS network (and we're definitely NOT using the mainnet), and instead advocating for the Australian Government to come up with their own Blockchain Network. Preferably the nodes would be scattered throughout government institutions and universities, which would lead to a nigh-indestructible-untamperable and extremely resilient database, very useful for many use cases within the government. In this presentation we present the use case as applied to IP Australia's current problem. We've talked a bit with the IP Australia team over how we could transform their current data into something more consistent (duplicated customers data).
Chatabout Joscar Toowoomba 1 1 # The Problem Many Indigenous languages have been lost and they are still disappearing. We spoke to an anthropologist who is an expert in Indigenous languages. He stated that the biggest difficulty in saving the existing languages is young people having no desire to learn them. **How can we work with Indigenous communities promoting languages and culture in a fun, engaging and playful way while being respectful to the culture?** # The Solution _A chat interface to Indigenous languages named Chatabout._ Chatabout has his own [facebook page](https://www.facebook.com/chataboutbot). Chatabout addresses the challenge to engage with indigenous community to promote languages of the first people. We built Chatabout to use the different language samples we found to interact with users. Chatabout is a chatbot that can be accessed though the Facebook page or directly by going to his [messenger account](http://m.me/chatabout) **Translation** Chatabout provides a simple translation service to give an understanding of the words it knows. It will translate English words to the indigenous language that you choose. For example `hand to yuwaalaraay` will return `hand in yuwaalaraay is Maa and is pronounced Mah.` **Game** The more playful skill of Chatabout is the game you can play with the bot. The game is a guessing game where Chatabout will ask you questions about indigenous languages in it's database. The user will then accrue points which Chatabout will track and tell the user if they won the game after 5 questions. #Technical Information A working prototype was built using Node.js and Chatfuel. It is hosted on the Heroku Cloud Platform. #Future Imporovements * Build to work at scale. * Expand the language database with new languages and new words. * Add additional text games that Chatabout can play with the user. **Chatabout aims to be a blueprint for linking the worlds oldest culture with some of the worlds newest technology.** The primary data used was from 18 languages and composed mainly of body parts. This data set was compiled by the State Library of Queensland. It came in the form of CSV files which we transformed into JSON to be consumed by our chatbot backend. We contacted an anthopologist who was an expert in Indigenous languages. He stated that there was once 600 languages across Australia. We find it heartbreaking that such a wealth of cultural knowledge is now so difficult to access. He also stated the this information exist. It is often a challenge to get though as it is often in hardcopy.
Clean city Team 200 Sunshine Coast (USC) 5 4 We are designing an app that combines spatial information about several sorts of waste management facilities in one easily accessible spot on your phone. The app inlcudes the location of: - publically accessible bins (green, recycling and landfill) - publically accessible toilets - bin collection days for your home address - automatic calender reminders the night before bin collection of your home address - drop off locations for the future SmartWaste system future implementations: - locations of recycling and green waste drop off location - Bar code scanning of items to recieve information on what type waste it is. (Does it go into recycling, green waste or landfill) - Accessing information on the producer and distributor of items and packaging by scanning the bar code of an item. This will allow investigation about where rubbish comes from. Open source sunshine coast council data was used for this project. The following data sets were used: - Public bin locations - Public toilet loactions - Bin collection days - SmartWaste drop off locations The datasets were downloaded and critical data extracted and saved as csv files. The csv files were layed over google maps. Our app links dirctly to this map including all information.
Climactic Climatic Sydney 9 7 The project aims to empower government, companies, social groups and individuals to make their well informed big decisions through existing Gov data. Government makes decisions every day—with long term consequences such as the location of a school, or on a small scale such as the rostering of helpdesk staff. Decisions from individual also matter, such as where to buy their first home. Such decision could make an significant impact to their rest of life. Climate change is here! How do we make this personal to the citizens of Australia through data? How do we show them the impact of rising temperatures, erratic weather patterns, increasing drought & floods, rising sea levels? Our solution consists of an immersive data experience through AR / VR to view the area of interest with data from Gov (climate and environment data) and private sector (real estate prices for example) overlayed . The viewer can then move a slider to change their risk profile, for example, to change the projected environment information and view this to make more informed decision. We provide a vision of the data platform as we see it evolving through continuous feedback via events like GovHack! **Here are a list of changes we aim to tackle** Bounty: Decision Support Bounty: Is seeing truely believing? Bounty: Making open data more open. More than apps and maps: help government decide with data Show Us The Numbers Data4Good SEED - Open Data with a Purpose What do you want from government data challenge? Urban Heat Challenge The main data we use consist of wetland of Australia, Temperature Data collected from Parramatta LGA, IPCC AR4 Sea Level Projections, House Prices from realestate.com.au. In this project, we have included wetland, temperature and sea level as our climate change factors/variables against house prices. For future work, we can scale the product to make other decisions other than property investment and include as many factors as possible. **Wetlands of Australia** Coastal wetlands are most at risk due to climate change. Understanding the impact of climate change and more specifically of sea-level rise on coastal wetlands must take into account factors that affect the ecological balance of wetland ecosystems **Temperature Data collected from Parramatta LGA** The temperature data set for Parramatta will be used to feed into the visualisation we have for the climate change. We want to use the information and also combine with a data set similar to climate [change in Australia](https://www.climatechangeinaustralia.gov.au/en/climate-projections/explore-data/data-download/gridded-data-download/) **IPCC AR4 Sea Level Projections** Projections for global averaged sea-level change for the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4) were based on global climate model simulations completed as part of an internationally organized set of climate simulations called CMIP-3. The Sea-level rise projection from 1990 - 2100 is used to calculate the water rising in and around sydney wet lands. **House Prices** The data is collected form [realestate.com.au](www.realestate.com.au). The data showcase prices of several properties in Parramatta suburb.
Community Skin Health Altis Canberra Canberra 4 4 Created a image classifying application to enable users to interact with a pre-trained model which gave them guidance on possible skin conditions. The application is designed to supplement existing government data sets to get valuable insights on community health trends. It also allows the community to engage more actively with the government using a medium they are already very familiar with. Using IOT devices is a smart way to gather data from users to build up a accurate data set. Combining this with AI and other pre-existing data-sets allows for all sorts of possible discoveries regarding data correlations. For example combining our data with sets from the bureau of meteorology or ABS occupation data could lead to new insights regarding environmental factors and community skin health.
Congestion Management System The Hackermen Sunshine Coast (USC) 7 5 We will use historic data sets that cover parking duration/occupancy, pedestrian traffic, congestion maps, and air quality, to establish a base line for congestion in the Noosa’s Hastings Street area. We will then develop vehicle counters to collect data in real time, to provide a live feed on car parking availability in the local area. We will also use air quality sensors to provide a live feed of the level of vehicle emissions in Hastings Street. Using roadside signage and online updates, visitors will be advised to divert to public transport or park’n’ride locations when there is low parking availability, or poor air quality due to excessive vehicle emissions, in Hastings Street. We utilised Noosa Parking occupancy and duration of stay reports from early 2018, additionally source data from google live traffic was used for this peak tourism and business time. DATA SETS WERE PROVIDED VIA EMAIL FROM NOOSA HUB !
Connected - Councils Connecting Community Just We Three Mount Gambier 8 3 'Connected' is a cost effective platform that councils can provide to residents, linking them directly with community groups, clubs and support services in their local area. The 'Connected' concept takes the form of an interactive, self-serve kisok that will be hosted in council libraries so that it is accessible to the whole community. 'Connected' is based on datasets that list all the many community groups and services available in a council's area. The program used by the touch screen kisok computer takes this list and makes it user friendly by taking a person through a series of prompts to connect them to the most relevant community group or service. 'Connected' has the potential to improve the mental health and physical wellbeing of citizens, and in doing so lower the downstream costs of health and social services. Most importantly 'Connected' has the ability to help councils connect individuals, families and carers, building a stronger and happier community. The main dataset we used is the South Australian Community Services Directory, an unordered list of community services and groups available in different regions of SA. The data is presented in a very simple Excel format, and gives details of the organistation's address, phone numbers, website and basic services/interest areas they cover (eg couselling, support group, sporting group). We have taken this data and used a system to organise it in such a way that the general public can easily find the groups and services that suit their particular needs by answering a set of questions/prompts via an interactive touch screen program.
Correlation Explorer I adopted a puppy today but I'm still here hacking Melbourne 6 4 ## Problem Local and federal governments have significant amounts of data that they have opened for public use. We know that currently, these datasets are gold mines to provide unbiased education of young people on the world they live in, but aren’t accessible in a fun or even simple manner. In fact, they often require significant understandings of data analysis to make sense of. ## Solution Correlation Explorer is a website that allows users to find trends between different data variables from open data. For the purposes of this challenge, users can upload their own datasets to find correlations on our graph. In the future, our recommended datasets will also be uploaded for use. As seen by the success of a viral correlations website (Spurious Correlations), the first step to engagement is creating something people want to engage with; something fun and user friendly. This can benefit young people looking for some fun relationships; for example, while building this program we found correlations between number of dentist practices and child protection services, as well as number of liquor licences and kindergardens. However, this data can also expose and quickly validate important issues; we found correlations between Indigenous populations and unemployment, as well as single parents and decreased personal incomes. ## Vision The possibilities of datasets used are endless, and we encourage local governments to send in their own data. In the future, we aim to upload a large dataset for the user’s use, and to add interesting information on each variable below the graph. The room for future education is infinite; the first step is to engage. To create and test this program, we merged multiple datasets including the 2011 Town and Community Profile Data, the Yoga Pilates and Tai Chi in Victoria, as well as the Liquor and Gaming License, and created a large single dataset to test and track correlations.
CouncilPlus The Codefather Sydney 5 10 <br />&nbsp; ## ❓The problem We're the Codefather team from Terem Technologies. With CouncilPlus we want to solve the problem of open source data access regarding the correlation between funding, services and societal outcomes across local governments. <br /> Currently, information about government spending by the council is fragmented. Each council must submit annual reports which outline their revenue, expenditure, and funding. But these reports do not demonstrate how this funding is translated into specific initiatives. Moreover, each state has their own standards of data sharing and comparisons of services across local councils. <br />&nbsp; ## 💡 The solution CouncilPlus: an open-source, aggregated, free dataset which is a consistent means of offering instantaneous access to relevant statistics for local government areas. Using our simple framework, councils all over Australia can use the data to collaborate with each other, share best practice and identify gaps to more effectively lobby for more funding and services. Additionally, we have created a channel for councils to interact directly with the federal government to raise awareness about issues being facing by their communities. We have used 10 data sets across crime, education and health, and our solution is built in React and Node.js, hosted on Heroku. Our tool, CouncilPlus, is a data visualisation framework that allows for council data comparisons with a click of a button. Where councils are able to identify gaps, plan their funding applications, and petition the government, in the spirit of open-source, so can local residents. This system can further assist councils to recognise areas of concern or interest in their communities. You can also see what petitions have been started in your area and join your neighbours in showing your support. <br />&nbsp; ## 🚀 Future milestones We have started with the datasets for the seven local government areas of greater Sydney, but we plan to expand this to all 537 councils across Australia. Future milestones include building an API to connect our petition-building capability directly to the government’s current system, E-Petition, to work with subject matter experts to improve the awareness indicators and identify trends, and to move away from the historical data collection model to real time. 🖖 We’re the Codefather, and we’re hoping in the most positive way, that we are making councils "an offer they can’t refuse". The Codefather has a diverse team of nine members across different areas of Sydney and realised although we cared about the same things related to our communities (health, safety, access to hospitals, schools etc) there wasn’t a single source of truth to compare each other’s areas to see where there were gaps in service. The data clearly shows there are disparities in services across services areas, and our desire to do something about it was the catalyst for building in the petition functionality. Once the challenges were announced, our team decided to use the data to identify any gaps in service and build a tool to highlight these gaps so action could be taken. Next, we used the government’s own priorities as related to the 2018 budget, third priority “Guaranteeing the essential services Australians rely on” to. Lastly, we looked at the challenges themselves and there was a common pattern of using novel technical mashups, making data more useful, telling the stories of Australians and sharing those stories with the greater population, and contributing toward the greater good. By focusing on safety, education and health, we believe we have a solid foundation on which to add even more datasets and expand reporting indicators, as well as having met the criteria of each challenge we have entered.
Crashboard as.numeric Casey 4 4 Crashboard is an interactive dashboard designed to take the guesswork out of decision making when local and state governments invest into road safety upgrades. Crashboard assists key decision makers in making data-driven decisions based on the identification of crash hotspots in varying weather and light conditions. Each local area is ranked based on a ‘road safety’ score, which could be used to identify areas in need of road infrastructure upgrades. The ‘Action’ tab within Crashboard highlights areas of concern within a given council area, and proposes potential solutions to reduce the crash-incidence rate and save the lives of Victorians. Together with Crashboard, we can help people get home safe. To develop Crashboard, City of Casey Transport Data was combined with Victoria in Future data tables, VicRoads Crash Stats and VicRoads Crashes Last Five Years. Starting with the City of Casey Transport Data, the crash database was used to identify road safety incidents in the Casey Region. VicRoads Crashes Last Five Years data was also added to give a Victoria-wide view. Weather information from the VicRoads Crash Stats data was joined to the main data set to gain an understanding on how weather impacts on road safety. Finally, population per Local Government Area was added from the Victoria in Future data tables. This is used in conjunction with the number of crashes per area to generate a “road safety” score, allowing comparison of road safety between different Local Government Areas, such as Casey council. Combined, this data becomes a comprehensive overview of road safety incidents in Victoria that can be used for discovery and comparative analysis as is done in Crashboard.
CrowdQuests Happy Goats Launceston 10 13 CrowdQuests is a game which has quests and missions to encourage physical activity and learning about points of interests. The quests are designed for: &nbsp;<br/> * Learning about locations * Crowdsourcing data updates * Crowdsourcing new information * Knowledge about problems * Encouraging certain behaviours &nbsp;<br/> CrowdQuests can be used by councils, agencies and corporations to crowdsource data and geospatial audits through a game interface. The game engine uses predictive user behaviour to encourage increased activity and usage. Challenges and missions can be submitted along with data sets. &nbsp;<br/> Google Slides Presentation Deck: https://docs.google.com/presentation/d/1OGvhWiLIrx4YfrIvqu7yRJWH4hc3WvL1cVVN6ckPSHI/edit?usp=sharing &nbsp;<br/> We have used a bunch of data from Launceston City Council (and can do the same from Hobart City Council) to load up a base layer on our map. It provides the opportunity for players to update details about what is shown on the map based on Quests that will be promoted to users based on their location and demographic. The demographic data and behaviours are preloaded into our algorithms to provide better Quest suggestions. Data from ABS and G-NAF and various other jurisdictions were used to work this out. &nbsp;<br/> New data provided by players will be then reported to the relevant jurisdictions. &nbsp;<br/> Photos taken would be processed by CrowdQuests servers using image recognition to produce rich meta data (including geotagging).
Crowdsourcing data audits Happy Goats Sydney 10 13 CrowdQuests is a game which has quests and missions to encourage physical activity and learning about points of interests. The quests are designed for: &nbsp;<br/> * Learning about locations * Crowdsourcing data updates * Crowdsourcing new information * Knowledge about problems * Encouraging certain behaviours &nbsp;<br/> CrowdQuests can be used by councils, agencies and corporations to crowdsource data and geospatial audits through a game interface. The game engine uses predictive user behaviour to encourage increased activity and usage. Challenges and missions can be submitted along with data sets. &nbsp;<br/> _We are aware we are not eligible for prizes/awards but are keen to help your agency crowdsource data audits and/or change behaviour through a game_ &nbsp;<br/> Google Slides Presentation Deck: https://docs.google.com/presentation/d/1OGvhWiLIrx4YfrIvqu7yRJWH4hc3WvL1cVVN6ckPSHI/edit?usp=sharing &nbsp;<br/> We have used a bunch of data from Launceston City Council (and can do the same from Hobart City Council) to load up a base layer on our map. It provides the opportunity for players to update details about what is shown on the map based on Quests that will be promoted to users based on their location and demographic. The demographic data and behaviours are preloaded into our algorithms to provide better Quest suggestions. Data from ABS and G-NAF and various other jurisdictions were used to work this out. &nbsp;<br/> New data provided by players will be then reported to the relevant jurisdictions. Photos taken would be processed by CrowdQuests servers using image recognition to produce rich meta data (including geotagging).
Ctrl-Access Team 41 Melbourne 4 4 **Ctrl-Access - Control your data, Access data relevant to you** Our project focus is empowering individuals to take control of their interactions with government data, and to mine their personal data. We do this through *a configurable, secure client.* The client can interact with user data, government data and user configured options to make pertinent data available through Alexa voice query and custom query forms. Ctrl-Access is a *modular reporting platform* on government and personal data. We envision an open 2-way marketplace where developers can create lifestyle modules that link specific data sets with different lifestyle ideas. For example, how does an individual's activity data stack up against the activity data for long-lived individuals, or how could a person with specific floral allergies move safely and comfortably through a city? Individuals can subscribe to these modules as appropriate to their lives. With thanks to Telstra Data Labs, especially Ryan and John, for their help throughout the weekend. **Ctrl-Access** The wealth of data on all aspects of society and the individual presents a unique opportunity to improve the quality of life of Australians. We are interested in empowering individuals to engage with their personal data and compare with government data in ways that will provide insights for their lives. Ctrl Access will enable users to interact with government datasets in a way particular to their individual data profile. Our demonstrated use-case is for an Accessibility Module. Given the requirement of needing wheeled access to buildings and public transport, the Accessibility Module checks building data and transport routes, as well as pedestrian volume along the route. Another potential use-case for accessibility is around the avoidance of environmental allergens, such as London Plane trees. We also envisage Ctrl-Access as a way of optimising health and well-being, as with [this video](https://www.youtube.com/watch?v=7c8O_XqZf78) where Alexa is interacting with the user about a computer game. Like the video, where he wants to know how to improve, and Alexa compares his data to everyone’s game play data and makes suggestions, Ctrl-Access will compare a user’s data to existing datasets to make lifestyle recommendations. For example, based on what Ctrl-Access knows about you and on the datasets it has access to, it could suggest tailored activities based on your demographic profile and preferences.
Cutting the Queues Weekend warriors Sunshine Coast (USC) 4 7 Our project aims to provide greater access to government services by reducing the demand for face to face appointments at government services. File corrupted, original full length video https://www.youtube.com/watch?v=sf0BUEq4ev0 Our project aims to make the front page of government services contact page to consist of 5 options. The first 3 options will consist of contact with relevant government agents either locally or, if via phone/internet nationally, with their wait times listed next to the option to encourage use of the least congested option, whilst the last 2 options will be a self service system utilising internet and SMS with no wait time and helpful step by step instructions. The first 3 options will operate on an appointments only system, inform users of necessary documentation, and provide a time estimate for their chosen process. We utilise; -Existing government centre locations and public transport data to provide users with routes and transit times to their closest designated government centre. -Historical and up to date data of centre wait times to provide users with an estimated wait time. -Up to date weather data to inform users of weather issues associated with their chosen service. -Queensland traffic data is used to provide a transit time for public and private vehicles to assist in arriving at a government service centre in time for their appointment. -Bus stop locations are used to assist in public transport transit to the government centre.
Cykel #overachievers52 Melbourne 2 4 Finding a common link between Ballarat and Denmark - cycling. A game that helps you explore the differences and similarities of the two places, by playing a challenging (and silly) game. The game will utilise bicycle usage data in both Ballarat and Denmark as well as live wind speed data to influence the game.
Data 88 88 Sydney 3 4 Improving search relevancy and discovery, to make data more accessible to the wider public. We utilised the existing data.gov.au search data, and combined it with external data sources such as Google Trends, Twitter Trends and News outlets; we aimed to bring data sets of relevant interests to users who don't entirely know what data to look for and how it might be useful, as well as speeding up the process for people who have direct needs.
Data Analysis in Cold Blood The Kwelamen Melbourne 1 3 The story of my failed attempt to find an amazeballs solution for Casey's Crash Challenge Summary population data extracted Crash Data analysed and results presetned
Data enabled health and welfare We R Adelaide 1 2 Purpose of this project is to understand what could be learnt from connecting disparate datasets available with GP Clinics, Pathology laboratories, Government agencies and non-governmental agencies and devices. To understand the economic impact of connecting the varying datasets; and to provide a direction to leverage the latest technologies to save lives using the datasets. Healthcare industry records are kept in manual files such as text files created by GPs, different data types such as X-rays, MRI’s and CT scans. Imposing a common format across would be improbable and time consuming. The disparity in the datasets can be overcome by transforming into a common format after the retrieval for each use. Connecting the datasets would enable the health professional to see the required records when required. For example, a patient called Jane has been visiting a GP clinic for the last 10 years but never visited a hospital. Jane met with an accident and admitted in a hospital. The hospital staff have no information about Jane’s medical history whatsoever since the databases are disconnected and disparate. The solution is to connect the databases, which enables the emergency hospital staff to access Jane’s medical history. Accessing the medical history in a raw format is no use for the medical staff since it would be time consuming to read the medical history to retrieve the necessary information. Therefore, the data needs to be visualized to provide single over- arching view of all the data touchpoints, to establish patterns. Additional insights can be obtained if the personal health data from wearables, IoT are leveraged as well. According to AIHW statistics around 30% of patients are referred to specialists by GPs annually. This would be putting huge burden on the health budget. This can be reduced if the patients’ history can be used to prevent diseases. Preventative healthcare by making use of patient data would result in fewer visits to specialists and hospital admissions. Predictions of diseases much ahead: If we have long history of cancer patients, for example, then these data sets can be utilized to analyse and investigate to find any indications/anomalies which could have helped in diagnosing the disease much ahead using machine learning algorithms.
Data Science for Everyone Team 193 Casey 6 4 In the last decade, terabytes of information has been collected from various industries, not to mention historical data that has been collected for many decades. Organizations seem to be unsure of how they wish to use this data however, in the questions they wish to ask and the visualizations they wish to draw. There is a vast amount of untapped potential in this data, including the ability to more effectively handle finances of projects, more effective planning of projects and even the social impacts of particular decisions. <br /> There has been a lot of work in the last couple of years to explore the data that has been gathered utilizing a wide array of technologies, including Machine Learning, dashboards through tools like Power BI, and many others. A lot of these tools require specialist training or access to expensive subscriptions, and would generally be for the benefit of the organization itself. This is where our project comes in. <br /> We believe that there is a lack of available tools for the average user to understand their environment and how they could use data to build decisions to go about their day. There is also a lack of cross referenced data that could allow for novel correlations to be drawn. People like city planners could use a tool that allowed for merging of data sets to make decisions that not only took into account geographical feasibility and similar ideas, but the mental well being impacts on the community associated with the outcome of such decisions. #Drawing value from data# Data in a raw format is not useful in making decisions as it is so difficult to consume. The crash data for Victoria alone in the last 5 years as over 78,000 records. Without significant time spent on analysing, formatting and filtering the data (assuming those skills exist for an individual in the first place), the data can’t be used to assist in decision making. This becomes orders of magnitude more difficult when trying to merge disparate data sets which often come from different sources. <br /> There were three main requirements that need to be addressed to allow for the most effective comparison of data. ###Data visualisation - The key to more effective planning### Having tools that can display large sets of data in a way that a majority of people can read is an important step in making 'DataScience for everyone'. Even datasets with millions of records can be interpreted by the everyday person if it is presented in graphical formats. Use of colors, interactive displays, etc. are great ways of getting consumers of the information engaged. ###Key columns - Correlations between numerous datasets### In one of our case studies, we attempted to merge AIWH 2015 Local Government Area Profiles data with the Victorian crash data set. This proved to be impossible with the data that we had due to the lack of similar columns between the data sets. Our objective was to determine if there was a correlation between mental health data and traffic collision data, including: <br /> *The duration a person had been driving and the likelihood of being involved in an accident. *The state of mind a person was in before having an accident. ###Complete data - Consistency, presence and accuracy### Ensuring that records have accurate data is paramount to finding relevant trends. In the Victorian Crash Data dataset, we found some columns in particular rows had not been filled in with a valid value, for instance the day that the collision occurred. Fortunately the number of records without a recorded day were minimal, so the impact on any conclusions drawn would be of little impact. It does however lead to trust issues with the data, and a requirement to perform data wrangling to get it in a workable state. Ensuring that key fields are mandatory when entering the data will help to protect the records from missing critical data. <br /> Often when trying to make use of large datasets, it can be found that particular information simply hasn’t been recorded. Having mechanisms that allows for feedback on desired data will help the parties gathering the data add in necessary fields into whatever forms are being submitted to the database. An example of a feedback form could be: <br /> *Field name: What would the title of the column be. *Field data: A description of the type of data that would be captured. *Reason: Why does the person requesting the data want it? What benefits would it bring? *Suggestion for acquisition: If the suggester has ideas as to how the data could be gathered, this should be included. <br /> Using the format suggested above, we could request for drivers awareness prior to the crash to be added with the following: <br /> *Field name: DRIVER_AWARENESS *Field data: A numerical value that indicates how aware the driver was. Could be based on open their eyes were, how many blinks per minute, etc. *Reason: To determine if driver fatigue was possibly a contributor to the collision. *Suggestion for acquisition: Sensor in vehicle, or wearable tech.
DataStat Our website brings all the data to the yard Sunshine Coast (USC) 4 3 Our project is a website database that aims to allow users to search, view, and download raw data which is scraped and cleaned from existing open data portals and catalogs. The site will compile data from existing individual databases all in one location, saving valuable time when searching in the field. DataStat will include existing metadata and value added search and usage metrics on each set of raw data and use this to rank the data against similar sets. Our design requires the use of meta data of datasets that have been sourced from CKAN metadata API's. Once the data is acquired an algorithm generates additional metadata from previously un-utilised variables. The data and the metadata are run through statistical analysis software with an integrated visualisation package where it is uploaded to the website for public use.
Dedupe me TinyIdeas 💡 Remote VIC 2 2 Machine learning based entity resolution to the rescue Databases somehow always end up with duplicate entries but we can solve that using machine learning based entity resolution (a.k.a record linkage, fuzzy matching, etc). Entity resolution typical requires: 1) Deduplication (removal of exact copies of records) 2) Record Linkage (records that may reference the same business) 3) Canonicalization (ensuring data with more than one representation are in a standardised form) Only steps 1 and 2 were addressed during this challenge of which out of 47404 records, 1920 unique businesses were identified using csvdedupe (https://github.com/dedupeio/csvdedupe) Perhaps you can even use this during form filling and validation to reduce any further duplicates. NB. Using Excel for step 1, and csvdedupe for step 2 which is simply a CLI program the only evidence of work is the training data generated by the program.
Discover Darwin Four 21 Darwin 6 6 The Discover Darwin project aims to support economic development in the Territory by helping skilled migrants match their lifestyle preferences to suburbs in Darwin. It gives prospective residents a taste of the uniqueness of the Top End and better prepares them to embrace life in the Territory. The project translates open data into easy to digest information relevant to the user. Data from the NT Department of Trade, Business and Innovation and the Australian Bureau of Statistics gives the user a snapshot of employment and demographic information in the NT. Data from the Darwin City Council helps users get a picture of the greenspace and culture in Darwin and individual suburbs. The data can be manipulated by the user for personalisation. It is presented using infographics and a story telling approach. Significant potential exists for the incorporation of additional data sets.
Discover Melbourne AR #overachievers52 Melbourne 3 4 Focused on helping people with ESL, to find like-minded communities, events and services. Focus is to design an app that transcends languages. One of our group members was in China last week and she felt completely lost - no English on signs or buildings and very little English spoken by the locals. We know how hard it can be to navigate a new country when you don't speak the language, and the rich multiculturalism of Melbourne results in a huge number of tourists visiting our city. We took as many geo-location data sets as we could find from free wifi, to green spaces, activities, and public transport routes, and combined them in to an app that helps as much as possible in the users own language, and through the method (2D map or 3D AR) they are most comfortable with. We also tapped in the Wikipedia knowledge base by providing links to landmarks and other locations in the users own language. Our goal is to also incorporate live translations via camera as well as a quick voice translate, where you can press a button to record speech (in either your language or the city's local language) and that will be translated to text, so you can quickly communicate with a local.
DiscoVR Technotelecomnicon Brisbane 5 5 # DiscoVR We believe that to live a healthy and active lifestyle is to embody the spirit of adventure. DiscoVR allows users to live out new adventures around Australia in a VR environment, before living them out in the real world. DiscoVR empowers Australians to make better decisions, allowing them to make the most of their leisure time and engage in physical outdoor, community-based activities. Our system makes use of publicly available data to find the right location, in the right weather conditions, with the necessary amenities, whatever your hobby. DiscoVR is a contextually aware virtual reality platform that provides benefits that can be applied across a number of industries: tourism, event management, and conservation to name a few. DiscoVR constructs an audio-visual experience which represents all the details relevant to your next adventure. Data is brought to life through a VR environment which immerses the user completely. The data available to us can enable us to live better and more fulfilling lives, but it is often presented in ways which cannot be easily digested. In the Information Age, our challenge is to make use of the wealth of information available to us to create real-world outcomes which empower communities and individuals. DiscoVR addresses this by presenting data in a virtual 3D format, immersing the user in a visual and aural experience. We display this not with numbers and graphs but with clouds, wind, rain and sunshine. ### How does it work? Users initially select from a range of activities based on their interests. The DiscoVR algorithm then accesses government data to locate the optimum location of the chosen activity based on the user’s location. For example, if the user wanted to go surfing, DiscoVR would consider wave height, wind strength and direction, and tide times to calculate an optimal destination. DiscoVR then takes information related to that activity and displays it visually inside of a VR experience. With surfing the user can see and experience the waves, rain and sun levels. The ability to visualise and experience data is not just useful for individuals planning their adventures. DiscoVR has utility across industry, and we can apply this proof of concept prototype across areas such as farming, event planning and conservation. A farmer may be able to use DiscoVR to gain an immediate visualisation of soil quality, water levels and potential crop yields. Event planners can quickly scout out new locations immersivity. Conservationists can view relevant scientific data in a virtual representation of the field. We can use the world of big data to connect virtual and physical space. It’s time to look at new development pathways, jump forward and really make this data useable for the average person. That is what we have achieved with DiscoVR. We join together a variety of bits of weather data to inform the pursuit of weather dependent activities. Our story begins by finding a variety of surfing locations, as scraped from: ###Latest Coastal Weather Observations for Queensland http://www.bom.gov.au/qld/observations/coastal.shtml These are then placed onto Google Maps API: ### Google maps The Google Maps API allows us to visualize the world, and put users in their destinations. https://cloud.google.com/maps-platform/ We were then able to find a variety of weather information for each location from the following: ### Bureau of Meteorology We access information on local Queensland weather information through the Bureau of Meteorology. ftp://ftp.bom.gov.au/anon/gen/fwo/IDQ11295.xml ### Willy Weather Additional weather information is accessed through Willy Weather. https://www.willyweather.com.au/info/api.html The types of information accessed were: - wind speed (represented by leaves blowing through the speed) - wind direction (represented by angle of leaves) - rain (indicated by rain drops) - cloudiness (indicated by poly clouds) - wave height (used in prioritisation) - tidal swell (used in prioritisation) After a location was chosen we were then able to use the following datasets to provide new information about a scene: ### Gold Coast Car Parks Parking availability is an requirement for many adventurers. https://data.gov.au/dataset/public-parking-facilities-city-of-gold-coast ### Gold Coast Showers Publicly available showers are used to filter surfing spots. https://data.gov.au/dataset/public-showers ### Australian public toilets Public toilets information are used along with other relevant information to find ideal activity locations. https://data.gov.au/dataset/national-public-toilet-map This information can then be visualised into the Google Street View (use of street view data for 3D effect): ### Google Street View https://developers.google.com/maps/documentation/streetview/intro
disintergrating wrappers Alex Toowoomba 1 0 it is about how we could stop littering with wrappers that disintergrate.
Don't Make Me Wait Lucky Shot Sydney 3 3 A chatbot to help people make better decisions about where to go when they have a medical emergency. Medical emergencies are triaged by hospitals depending on the severity of the condition. This affects how long a patient must wait in an emergency department. We use data from: data.nsw.gov.au (Emergency department by Local Health District) health.nsw.gov.au Google APIs Through a simple chatbot interaction, we help people find the hospital where they are likely to spend the least amount of time waiting to be treated. As a result we hope to reduce bottlenecks in emergency department waiting rooms.
DON'T PANIC! Team 42 Canberra 1 1 Let's muck around in AFSA's insolvency data to see if we can find anything to predict non-compliance. The data yielded a few interesting features after some squeezing and ringing. Males are more likely to breach their insolvency conditions than females. People who give common reasons for insolvency are less likely to breach than those who give unclear reasons or don't give reasons. Business related insolvencies yield about double the proportion of non-compliance cases. Curiously, when an applicant states doesn't state their family situation as part of the initial insolvency, they are much more likely to breach its conditions.
EasyBiz ARVIS Melbourne 4 5 There are two types of end users will use our solution, the business owner can use our mobile app to find the place to start a new business or grow the existing business. The government can access to the web portal to see the where are the least business growth places in the country, the AI will provide with city improvement suggestions that will attract more business to come and help the existing business to grow. We have developed a simple machine learning model and a judging AI algorithm to find a best business location. For example, you want to open a café shop in CBD area, and your budget is 100k, Our AI will look for your business competitors around that area, your potential business streets should be a little bit further away from the existing competitors, you don’t want to open a café just besides another café shop. Then a few streets that have the café business capability are found. Then pedestrian volume and car park bays are the factors to be considered to analysis these streets, the AI will select a list of locations to the user based on the pedestrian volume and number of available car park bays from high to low. The future development of this solution would be adding more relevant data sets to the machine learning, more data learning model should be added and unsupervised machine learning could also be conducted in order to achieve more accurate place finding. The business owner may receive notifications that a few new places are available for business growing based on the latest government development plan. The government could receive notifications that infrastructural facilities in a certain area needs to be improved such as car park space, public transports. The solution utilises the latest Google Machine learning to analysis a few data sets such as Cafes and restaurants data, City of Melbourne population forecast, prdestrain volume, bar and pubs, on-street parking bays. We developed some supervised machine learning data models for the machine learning to extract the patterns and criteria that our application needs. The decision is made by AI based on the requirement from the user and the machine learning data.
EasyBuzz Parking MelbourneGo Melbourne 4 3 Our project aims to make it easier for and organisations (specifically the ATO) to target underutilized locations to set up their business (or tax help centre). We used live parking sensor data from City of Melbourne to discover areas that have lots of available parking, and combined this with ATO's data to show available parking in postcodes alongside demand for ATO tax help in each postcode (using number of people in 2021 (as determined by a linear regression on past years) who will be earning $1 - $2000 per fortnight as an indicator of demand).
Emergency Data Response TechPreppers Melbourne 3 4 This project is based on a device which will host emergency data related to a local disaster site. Basically a local internet which works in a situation where no internet is available. 1. Whole-of-Australian Government Web Crawl https://data.gov.au/dataset/whole-of-australian-government-web-crawl This data set is the static source of whole of Australian Government websites. The total memory is about 66 gigabyte. Usage: The emergency group can access and host the government websites of only the affected location, which are helpful in providing the related information in the event of emergency. 2. 2014 town and community profile for Oakleigh South (Suburb) https://www.data.vic.gov.au/data/dataset/2014-town-and-community-profile-for-oakleigh-south-suburb This data set is an example data of the local community members in the affected location. It has the population, gender, age group, social demographic and geographic data. Usage: We get the local population distribution of the affected site based on age group, gender etc. So that the emergency group knows statistics of people who are affected. 3. State wise Cancer Data stats https://www.aihw.gov.au/reports-statistics/health-conditions-disability-deaths/cancer/data This data helps in estimating the cancer patients in the affected site by doing some estimates or analysis on state wise data. Let's say there are 10,000 cancer patients in Victoria. And by percentage population of the affected location, we can estimate the supplies which might be needed at that site. 4. Diabetes datatset in Australia 2000–2013 https://www.aihw.gov.au/reports/diabetes/incidence-type-1-diabetes-australia-2000-2013/data Just like cancer data, this data helps in estimating the diabetic patients in the affected site. So that supplies (insulin etc.) can be estimated.
Empowered Communities Technovators Adelaide 2 4 1. EMPOWER - Our idea is to empower the communities and to improve their engagement with councils. 2. CONNECT - Our idea also connects different community members through events and activities to improve their health and well-being. 3. ENABLE - Our idea also enable the councils to make better decisions using user generated data. We identified the assets data of local councils and the addresses of these assets in maps API and used them in our application to display the nearest assets to the user based on their location. We have used local councils' data of parks, open areas and community centers to visualise them using maps API.
EnVisible City Live+Smart Lab Wyndham 10 7 The problem: How to engage communities and citizens to experience quantitative and qualitative data on the tangible and sensory aspects of a city during different times? What makes a city a great place in which to live, work and relax? Sophisticated metrics have been developed on the component parts such as patterns of use, transport infrastructure and climate; these and a wide range of other data underpin our understanding of liveability. Such indices can be supplemented with text, photography to illustrate some qualitative aspects of place, however many of the intangible and sensory are very difficult to visualise and communicate. Our solution: The increasing ubiquity of virtual and augmented reality provide new opportunities to explore the multi-sensory and temporal aspects of urban place. We take government data of various aspects, which are placed as 3D models, vegetations, spatially distinct sound emitters that combine to generate a dynamic experience as the user moves through the scene. We also foreground the temporal character of urban place, with the intent of enabling the end user to ‘dial up’ different time and dates of the development and environmental conditions of the place. Prototype application: A prototype application has been developed that can be simultaneously broadcast to screen and surround sound systems, to allow individual and small group evaluation of city scenes. The application uses a haptic interface (oculus touch), which enables the user to hold a virtual smartphone as the interface. The menu includes a handheld map with hotspots to allow teleporting around the site, as well as free movement within the scene. User can also ‘dial up’ the time and dates, access videos that capture typical movement paths through the site, select and hold supplementary drawings and photographs. Datasets such as energy consumption can be viewed on the virtual map as well. Projected developments and events are developed in the VR space, and an interface enables the user to switch between and experience the proposed interventions. Future applications: The prototype demonstrates proof-of-concept and informal feedback from participants and observers; there is much potential to develop the approach to enable the qualitative aspects place to be used to engage with communities, business and industry during the early stages of urban design.
E-Thos Team 242 Canberra 4 3 E-Thos is a web based application that is designed to help potential/current business owners better understand the population demographics of the area that the business owner(s) intend to operate in. E-Thos takes in a location input from the user and then uses that information to provide a visualisation of competitors nearby. It then outputs to the user statistics and graphs that may help provide more insights with regards to projected population in the district of the given area. Our first aim with this project was to help current and potential business owners increase their prospects. One of the ways we thought about doing this was to use the geographical data from the G-NAF data set and others to help develop more insights on the population demographic that are within an area a small business owner could potentially target. The overall goal in achieving this was to provide the user with the locations of all the industry competitors in the area, as well as provide graphs that help explain population trends (total, by gender, by age group). Another aim that we hoped to achieve with our project and with the data we used was try and help the government understand where opportunities for small business owners could occur, and to help the government further encourage business growth. Our third aim was to encourage academia and government to work together to map out business opportunities, while government can also give academics/students problem statements to solve.
Everyday Active Death Clock Darwin 4 4 ### Overview We live in congested cities and can struggle to find the time to keep ourselves healthy. Why can't a little exercise be a normal part of our everyday lives? ### Commuting Commuting by car is both sedentary and contributes to greenhouse gas emissions. Research has also shown that sedentary commutes contribute to stress, high BMI and even cases of influenza. A little exercise by cycling on your daily commute on the other hand has positive impacts for both your mental and physical health. ### Get Active Everyday Active is our mobile application to encourage commuters to take a bike ride instead of a car, The Everyday Active App will make it more appealing for people to get out and active. It suggests interesting alternative routes from the easiest and shortest through to the fastest or more difficult pathways to take. The app will also display bike hire and parking outlets. ### Be Social If you want to grab a coffee on your way the app can display various places of interest for you to stop into and for weekend rides with friends, you can select from popular social routes. ### Challenge Yourself By providing interesting alternative routes we will reduce car parking demands and assist everyday Australians to increase regular exercise in their routines. We want to make it easy and fun to stay fit and healthy. ### Our Aim By making it easier to cycle, we will reduce car parking demands and assist everyday Australians to incorporate more regular exercise into their daily routines. We want to make it easy and fun to stay healthy and fit for both new and existing riders. Our team utilised the City of Darwin shared paths geojson data, along with SpinWays Bicycle Hire locations, and newly acquired bicycle parking locations that have been open sourced through the OpenStreetMaps platform. OpenStreetMaps was used to display all of the data and lookup addresses. The Open Source Routing Machine service was used to calculate point-to-point routes. OSM also provides point data such as elevation that can be used to determine the difficulty of a route. As we are utilising a development-only API, if we exceed our API request quota, we display a locally cached default route. The AIHW Australian Health Survey of Physical Activity was used to compare a users activity with the average activity of the broader population. This provides a positive benchmark to congratulate users following a ride, and interesting statistics to use in push notifications to get our users back on their bikes.
Expose: Show us your data Expose: Show us your data Adelaide 6 23 Group of data munching friends who have a shared love of solving problems using data. Let us expose it and make it useful. Show us your data! # GovHack2018Expose Team memebers: Etienne Oosthuyesen, Jean-Noel Seneque, Jake Deed, Andrew Exley and Cameron Wells Source Code url: https://github.com/ExposeShowUsYourData/GovHack2018Expose Video url: Homepage url: https://github.com/ExposeShowUsYourData/GovHack2018Expose ### Local Event Location: Adelaide ** Challenges: ** - Local - Improving Response - Best entry that assists CFS planning for and responding to incidents - Local - Emergency Planning and Response - How can we better plan and respond to emergencies? - National - Bounty: Mix and Mashup - How can we combine the uncombinable? - National - Bounty: Decision Support - How can we make it easy to use weather and ocean data to our advantage? (e.g. when should you lay concrete, or go out yachtting or picnicking?) - National - Working Together - How can open government data to improve responsers' situational understanding and ability to plan their response, and share their information between agencies? How can sharing information between agencies be improved by different information presentation, allowing more informed decisions during domestic emergencies or national security events? #### Data Collection and Identification: As a team we worked together to identify all the open licensed data sets, and Data Services we could freely use and re-purpose to meet the above challenges. Immediately we interpreted the challenges as needing mapping data sets; location based, as well as other real time data feeds. There's the data needed for preparation for those ready to confront whatever incident or emergency is occurring, there's the data needed to collect information about the incident, as well as peripheral data such as weather, rainfall\wind direction that is currently occurring. There's also the data to assist the services to reach the incident efficiently and safely, as well as those near the incidents to move away from danger as quickly and safely as possible. Once the relevant services are within proximiatey of the incident or emergency, they need continuous feeds of data to locate those injured or in danger, knowing where the exact front of the fire or emergency is, what risks are a factor, but also relying on constant communication to other emergency services, planes, applicances, volunteers and control centres. Basically, we wanted to find any data sets that may have been useful for any of these purposes. #### Using the data, merging together and making available for users and contributors With complex and different types of data sets, a necessary step is to land this data onto a shared platform, either using a traditional relation database platform, or more modern data stores like cosmos db which can handle semi structured data, to even something less complicated such as BLOB storage. Regardless of the platform, data can then be fed into a number of services using a real time messaging, or streaming service to push data out using a broker which can then be subscribed to by which ever agencies need it. The same source of data can be used by a number of agencies at the exact same time, seeing the same data, but potentially in a different format or application. i.e. A member of a CFS applicance may only want to know details of members of the same applicance, where as their regional chief, needs to know data about several appliances, and a control centre may need to know everything but in summary. All same data, all being pushed out at once, and can be used in different ways by different subscribers. Can also be used by Apps or reporting tools, but being stored in a database gains access to more complex processes like machine learning over historical data. The app can also play the role of data contributor too, allowing users to enhance the data further by inputting more accurate and real time substance such as if a fire or threat has moved, so that everyone can immediately subscribe and be shared the latest information. #### Going further than that! There is plethora of data that 'could' be collected to further enhance the challenge to plan and respond to emergencies even better. Having each vehicle, appliance, plane or helicopter to name a few, tracked by a device to publish to all involved where a vehicle is located at at any point in time, their fuel load and/or their water load (if water bomber or fire appliance). This could extend to individuals on the ground tracking where each servicemen is located, for a variety of benefits from a rescuing point of view, but proximity to the closest threat or person in need of rescue. More complicated devices could be used to locate people in distress either using meshing technology to locate a phone signal, or provide them with beacons so they can be located, with the beacons also sending data to the platform which can be used throughout the solution. Therefore, each entity within the 'environment of concern' can be located and tracked, therefore more complex algorithms can be used in combination of this data to find the best possible method of extracting those from danger, whilst focusing on retarding the threat. If a threat is a person or people, this too can be identified using facial recognition, and tracked and pin pointed using a variety of Artificial Intelligence API's.
FaceMap IDeEA lab Wyndham 9 4 Objective: Engaging with local community through playful visualisation of (geo-located) city data as parametric interactive abstract faces. Developing a mobile AR (Augmented Reality) app with two modes, where ‘Mode 1’ will be - translating city data as a parametric face of the city (neighborhood) and ‘Mode 2’ will enable the application of this city ‘FaceMap’ as a live selfie effect using Face Tracking AR technology. Problem: Each year Australian government collects tons of potentially useful and interesting data. However most this data lays dormant and is not being utilised, because most of the data is being collected, stored and communicated to public as those ‘boring’, hard to read spreadsheets or text files. The fact is that not all people are good at reading numbers and/or understanding and interpreting numeric or text-based data sets. Thus, en masse, public is reluctant to actively engage with this potentially valuable source of information. Opportunity: However humans are really good at reading faces and facial expressions. We use our faces to communicate complex information - instantly. It’s in our human nature. We wake up in the morning and we look in the mirror. What does our face tell us? Throughout history portraits played a crucial role in art and culture. We see faces on book and journal covers, advertisement and movie posters. Nowadays - selfies are integral to social culture. AR Face Tracking technology is extremely popular among available mobile apps, and live selfie effects (such as snapchat filters) are being used daily by millions of people (Snapchat alone is used be over 158 million people daily). Solution: Make data visualisation - engaging and easy to ‘digest’! Use data variables as generative face attributes. This projects taps into human natural capabilities of reading and understanding faces. The intent is to translate geo-located city data as (hopefully cute and engaging) abstract faces, allowing people to use the city ‘FaceMaps’ as selfie effects or view them as a combined map of data-faces [What is the face of your city?]. FaceMap prototype uses following data to visualise the "faces" of cities: ___________________________________________ -Total Population -Median age -median taxable income -Average Taxable Income -Median Rent (weekly) -Average Household Size -Total Private Dwellings -Employed -Dwelling With No Motor Vehicles -Education: Bachelor Level and Above -Average Total Business Income -Average Net Tax -Age of community (young-old) -Homeowner status (renting / paid in full / paying the home loan / etc.) -Occupation (student / working full time / unemployed) -Park (green) area in the city -Education level -Population density -Health level -Houses water consumption -Houses energy consumption -Average income -Number of sport facilities / public libraries / art centers ________________________________________________ Output 1: Mobile app generating an abstract face interpretation, where facial attributes are informed by local city data, including such data variables as: average age of community, homeowner status, occupation, park (green) area in the city, health level, sustainability of housing: energy and water consumption, average income, education level etc…. And allowing people to express and share their feeling and emotions regarding the current state of city ‘FaceMap’ by choosing happy/unhappy facial expressions that will be applied on this data-face-interpretation. Outputs 2: Mobile selfie effect app, which would apply chosen various city faces as masks, using Face Tracking AR technology. Allowing people to share these FaceMap selfies with the larger community, raising public awareness of current state of Australian cities.
Fail-a-corn The Real Slim Shady Sunshine Coast (USC) 8 8 Governments are good a regulating business but bad when it comes to providing guidance. It is on everyone's radar to grow the economy in areas of high demand or future need, but there is no real way of individuals knowing what will work where, so of all companies that start up, half fail within the first year. If the hard questions about <em>why</em> instead of just the regulatory questions about <em>what</em> were asked up front, new companies would begin their journey in much better shape. Using government grant and investment data to show which industries new businesses are best to start up in was in a 2016 project 'Unveil the Scene'. The same year the project 'Future Proof' used open data to give job seekers a greater perspective on where jobs are likely to be located before they are posted on job sites. This year our team is going to build on these previous works to develop a single pane of glass interface to guide those with a great idea, and turn it in to a viable business.
Feel the Burn! No GovHack for Old Men Launceston 0 4 Feel The Burn is a cycling game that uses an exercise bike to enable the user to ride courses that have been generated from open data sets. The original inspiration for the idea came from reflecting on what it means to really understand data. A key question we asked ourselves was: what if you were able to feel a data set by traversing it as though it were a landscape? Would you understand the data better? Would the experience be more memorable than other ways of exploring data? From there, we developed the idea for “Feel The Burn”. In this game, the player is able to ride along virtual tracks that have been generated using a range of different datasets. As the player rides up a hill, resistance is applied to the exercise bike so that the player can “feel the burn” as they push against the resistance. Where the data descends, the resistance is released that the player is able to coast downhill and build up considerable speed. As the player rides each course, billboards beside the road call out points of interest and help contextualise the data the track has been generated from. Feel The Burn was developed in Unity and incorporates an Arduino Leonardo which we use to sense wheel rotations on the exercise bike and also to control a servo which applies resistance to the bike when the player is riding uphill (and releases it when they’re coming down again). Our terrain is generated within Unity using real datasets (ranging from climate and environmental data, through to tourism statistics and water levels in hydro dams). A number of the datasets we chose were related to climate change and include strong linear trends. We took our title from the experience of riding up the slopes created by data relating to atmospheric carbon and annual temperature anomalies (both examples of data that has been steadily increasing over long term trends). However, we also included some other kinds of experiences in our game. Riding the terrain we’ve generated from the decreasing landmass in Greenland is the opposite experience, with the player riding downhill almost the entire way. Once we’d prototyped a few experiences that related to climate data, we decided to throw in a few bonus levels where we fed different data sets into Feel the Burn to see if we could create some interesting riding experiences. One data set that worked well was tourism visitation data. We grabbed historic information about the number of visitors to Australia from China and used that to generate a new track in the game. This track is particularly interesting, as it combines a long term upward trend with the seasonal effect of tourism booms in January and February each year. Our final experiment was to take water level information from a particular Hydro dam in Tasmania and create a track based on the rise and fall of the water level over time. The particular dam we chose, Lake MacKenzie has completely filled and completely emptied a number of times during our period of interest, creating a track with many hills and valleys for the player to ride. We sourced our Australian climate data from the Australian Bureau of Meteorology and our international climate data from NASA. We sourced our tourism visitation numbers from Tourism Australia. We sourced our hydro energy storage information from Hydro Tasmania. Background music in the game and video is "Summer" from bensound.com
FirstResponders FirstResponders Remote SA 4 5 Provide a consolidated view for the CFS volunteers to access critical information during an incident or when in a strike team The context and objective of this project is to provide a consolidated view for the CFS volunteers to access critical information during an incident or a strike team and that will assist CFS planning for and responding to incidents. The machine learning model used considers the datasets from Bureau of Meterology, previous incidents responded by CFS, sources of water like Dams, rivers, accessibility to properties and other parks , roads information. This provides Artificial intelligence and way to identify fire patterns and plan for crews accordingly including support agencies during peak fire seasons. The app will also provide the nearvy fuel stations, the Incident controllers, the staging area location and different sectors involved in the incident. The application will also consolidate the emergency management data which includes logisitics, shift rosters etc and provide a consolidated view for the crew on the ground. The suggestion is also to link the mobile application or have a notification mechanism by having a IOT device in vehicles which will notify the ESTA automatically in case of a major collisions or incidents,. This will help in rural areas where number of transport road users are less. This will be done based on IOT sensors placed in vehicles and common locations. https://drive.google.com/open?id=1zyBaJqVIbTN-QbNsWJqWhGZwluDZNCDL
From Global Climate Change to Future Ocean: Geospatial Local and Nonlinear Impacts of Ocean Flows and Human Activities on the Ocean Climate and Environment, and Spatiotemporal Decision Making for Marine Ecosystems Future Ocean Perth 7 6 ## Objectives This project integrates spatiotemporal statistical models and machine learning methods for predicting future ocean climate and environment scenarios and the decision making for marine ecosystems. ## Methods (1) Geostatistical methods are used for spatial prediction of variables (2) Generate spatiotemporal dynamic maps of ocean climate, environment and the relevant variables. (3) Geographically weighted regression (GWR) is used for exploring the geographically local impacts of ocean flows variables, environmental variables and socioeconomic variables on the ocean temperature and salinity. (4) Machine learning algorithms and geospatial nonlinear methods (geospatial generalised additive model (GAM)) are integrated to assess the geospatial nonlinear impacts. (5) Geospatial decision making is performed for spatiotemporal decision making for marine ecosystems. Develop an online interactive geovisualisation and decision-making system. ### Project Report can be downloaded at https://github.com/zacksong/GovHack2018_FutureOcean.github.io/blob/master/Future%20Ocean%20Report.pdf ### Video https://www.youtube.com/watch?v=d_ge7DupGoo ### Dynamic spatiotemporal maps https://github.com/zacksong/GovHack2018_FutureOcean.github.io/blob/master/Dynamic%20spatiotemporal%20maps.mp4 ### Mulit-source variables map (can be printed with A3 paper) https://github.com/zacksong/GovHack2018_FutureOcean.github.io/blob/master/Mulit-source%20variables%20map.pdf ### Data and application https://github.com/zacksong/GovHack2018_FutureOcean.github.io/blob/master/Data%20and%20Application.png ### Geographically local impacts https://github.com/zacksong/GovHack2018_FutureOcean.github.io/blob/master/Geographically%20local%20impacts.tif ### Geospatial nonlinear impacts https://github.com/zacksong/GovHack2018_FutureOcean.github.io/blob/master/Geospatial%20local%20impacts.tif ### Graph Abstract https://github.com/zacksong/GovHack2018_FutureOcean.github.io/blob/master/Graph%20Abstract.JPG ## Results The results of the project include: 1 |GovHack Project Homepage| Description of the project 2 |Project Report| Details of the methods and results 3 |A Graph Abstract| General ideas presented by a graph 4 |Maps and New Datasets |Multi-source data integration 5 |System| Online interactive geovisualisation and decision-making system 6 |A list of recommendations| A list of future research and application ideas based on this project The results are explained in the following sub-sections. ### Spatial Variables In this project, the ocean climate and environment are quantified using ocean surface temperature and salinity data, respectively. To explain the potential variables that affect the ocean temperature and salinity, two categories of potential explanatory variables are collected from multiple sources, including Australian government open data, remote sensing data, and other open data. One category of explanatory variables is ocean flows information, including zonal (eastward) velocity component, meridional (northward) velocity component, and surface height on t-cells. Another category is about human activities, including shipping activity density, locations of ports, offshore oil and gas platforms and activities, and locations of populated cities. To evaluate the impacts of ocean climate and environment on the marine ecosystems, the ocean biovolumes data is collected and visualised. The above data sets and spatial variables are mapped in Figure 1. This map with high resolution and can be printed with A3 paper is uploaded on the website. Figure 2 presents the 3D time series of the ocean climate and environment variables with the example of temperature. Figure 1. Map of the ocean climate and environment variables and the explanatory variables Figure 2. The 3D time series of the ocean climate and environment variables (temperature here) ### Spatiotemporal dynamic maps The spatiotemporal dynamic maps of ocean climate and environment variables are generated as a video: Dynamic spatiotemporal maps.mp4. ### Geographically local impacts analysis Figure 3 shows the geographically local impacts of ocean flows and human activities variables on the ocean climate and environment that are explored using the geographically weighted regression (GWR) method. Results show the impacts of different variables have significantly varied impacts across space. Figure 3. Geographically local impacts of ocean flows and human activities variables on the ocean climate and environment ### Geospatial nonlinear impacts analysis Geospatial nonlinear impacts of ocean flows and human activities variables on the ocean climate and environment are calculated using geospatial generalised additive models (GAM). The GAM model is performed using R. The results are shown in Figure 4. Results show that the explanatory variables have significant nonlinear impacts, and the impacts are varied with the locations and the velocity components in two different directions. Figure 4. Geospatial nonlinear impacts of ocean flows and human activities variables on the ocean climate and environment ### Geospatial decision making, significance and potential applications of the study In terms of the above results, the geospatial decision making, significance and potential applications of the study include the following parts. - Provide methodologies, data sets and quantitative evidence for researchers and marine industries’ more accurately and geospatially local exploration of oceans. - Provide quantitative basis for the spatiotemporal decision making for the management of ocean environment and marine ecosystems. - This project provides a benchmark for the collaboration of industries and academia for addressing a sophisticated problem about ocean environment and human activities. The project brings ideas, knowledge, technologies and decision making from both industries and academia. In general, industries have rich practical experience and knowledge in certain fields and developed skills of technologies. Academic researchers are expert in proposing new concepts, theories and methods, and developing new tools. In this project, the industries include government agencies and companies of ocean environment protection and management, marine ecosystems monitoring and management, ports management and shipping industries. Academic researchers can provide new methods for spatiotemporal data analysis and decision making, manage and update database, explain data-driven results with professional knowledge in ocean, environment, ecology and human activities. - This project provides a benchmark for applying the methodologies and outcomes in the relevant studies in other regions in both Australia and the world. Figure 5 shows the application of the methodology and data sets for the ocean in the western part of Australia. The methodology and outcomes also can be applied in other parts of the world where ocean climate and environment are of important concerns, and human activities are dense, such as offshore oil and gas industries. Figure 5. Application of the methodology and data sets for the ocean in the western part of Australia
Game of Throwns Litter Louts Melbourne 3 4 # Spring is coming for recycling We have a waste crisis. Only 32% of Victorian household non-garden bin content is recycled, according to Sustainability Victoria. It is everyone's problem: manufacturers and retailers; household consumers; and waste managers. Despite the means to do so much better, so far we do poorly. But if we **play** fairly, we can all be the solution. Let's play **Game of Throwns**. It embraces the world of gamification to make awareness and change behaviour around waste _fun!_ ## At the supermarket.... It's a sort of **green loyalty card** as well, allowing participating retailers to reward customers who hit high recycle use rates at the checkout. Once all their goods are scanned, the customer receives a docket with a grand total of what proportion of their list is recyclable. The docket might even break down, line by line, what is recyclable and in what manner. ## At home... At home, the game is more an honesty system. Householders do it because it is fun and satisfying to do better. They scan the barcodes of waste using the Game of Throwns app on their phone. They will learn what proportion of their recycled purchases was _actually_ recycled, plus whether they beat the average Victorian and even person in their council area. We'll even tell them if they can recycle better than a Pom! And for extra buzz, households can share scores. Kids can push parents and grandparents to do better. Plus, the details of scanned binned items can be added to a shopping list, allowing households to modify the contents of the weekly shop to more sustainable goods over time. ## Advantages of approach This project has the capability to start small and **scale up.** Find one supermarket that is willing to participate in a trial. They get a huge reputational reward through all the traditional and social media interest. Perhaps even offer them a commercial rates discount to be involved. Over time, other retailers will want to join or risk been seen as a laggard. The game gives policy makers **real time** data about the purchase of recyclables, plus a database that just _keeps_ growing. ## Phase 2: sound of sustainability As the scheme is rolled out and matures, it can use other new technology such as home listening devices e.g Google Home and Amazon's Alexa. Owners of these machines can ask "Is this _Cow's Best Milk_ milk carton recyclable?" and the Game of Throwns database will be the go-to-place for these devices to find the answers: "yes, according to Game of Throwns and Sustainability Victoria, the carton of _Cow's Best Milk_ is recyclable. Please place in your recycle bin. By the way, it is bin night tonight!" Sustainability Victoria is the primary source of data. A key database is the _Diversion Rate, Victorian Local Government Annual Waste Services Report 2015-16_ which will be used for benchmarking individuals. We'll also use the **equivalence** data from the kerbside calculator to make some of the environmental achievements easier to appreciate. The solution will access an open source database of barcodes. It will also access UK waste data information to give an international benchmark for our players. But the real story will be the game's ability to generate its own **data goldmine.** Over time, a rich store of real time intelligence will be built.
GCLink GCLink Gold Coast 5 4 We will focus on the utilisation of roads and transport in the Queensland State Government level, primarily on the Gold Coast where there have been recent investment in new transport options in light rail and bikeways. By understanding the difference in traffic levels for districts with more accessible public transport and alternate travel options (like bikeways or autonomous vehicles) the government can better substantiate new investment in expanding their transport options. The combined data sets are from various modes of transport, parking, public sentiment, and geospacial traffic maps. Councillors are interested in traffic comparisons that dictate where their transport investment should be made and what modes of transport will be more beneficial. This will dictate forward-looking government backed green initiatives, reducing congestion, road upgrades and ease of mobility for tourists and attracting residents. We will use our base idea of improving transport solutions and investment in roads, which has many obvious datasets like location of cycleways and light rail utilisation. We will explore the available data on council, government and open data from industry to discover patterns that can correlate seemingly unrelated datasets like development history in the different districts, weather and tourism along certain routes etc to help tell the full story of our transport utilisation recommendations. How can we use open data to use evidence based decisions?
Geoffrey, Your Friendly Property Safety Adviser ChatBot LiveTiles Team B Hobart 4 9 So…you have decided to buy a house! What a great idea So you think you know what risks are involved? That’s where you are wrong! What about all the potential disasters you can’t foresee?….well now you can, with Geoffrey your friendly property safety advisor! He’s the friendly no-fuss bot that can do all the hardwork for you! He searches through huge amounts of data to see if the house you are looking at is at risk from: flash flooding or rising sea levels - from climate change Did you know a landslip zone can stop you from being able to rebuild your house? He can even know if you are at risk of bushfire! But don’t worry Geoffrey is here to help and guide you in choosing the right property to suit you… Geoffrey is a ChatBot, Chrome extension that queries 9 data sets to provide helpful insights about properties a customer is looking at. The ChatBot gets out of the customers way until it notices they are looking at a property that may cause headaches if they were to purchase it. Some of technologies we leveraged: - Microsoft's natural language understanding platform - This let's us interpret what users are asking the bot - Microsoft's QnA Maker - Question and Answer knowledge base system - Microsoft's Bot Framework - Gateway for bot messaging - Azure Functions - Hosting our service that calls dataset apis and normalises the responses. We query 9 spatial data sets on 'The List', a portal for state data. The datasets we chose to use, provide information that would be useful to know during the process of buying a house. Tasmanian Heritage Register - If a property is heritage listed there are restrictions on what modifications can be made. Coastal Inundation Mapping - Is the property at risk of flooding in a storm or high tide? Coastal Projected Sea Level Rise - Is the property going to be effected by rising sea levels? LIST Easements - Are there any easements on the property? Bushfire Interface Areas - Is the property at risk of bush fire damage? Tas Water Dam/Reservoir Flood Inundation Summary - Is the property at risk of being damaged by a flood from a dam or reservoir Landslide Planning Report - Is the property on a known landslip area? Cadastral Parcels - We used this dataset to determine the bounds of properties Coastal Erosion Component - Is the property at risk of damage from erosion?
Get Active Get Active USC Sunshine Coast (USC) 10 10
Go Go Tax (GovTax) Go Go GovHackers - Tax Melbourne 2 0 GovTax helps verify if the ATO has optimised the location of Tax Help centres to benefit the intended clients. We've upgraded Alex, the ATO's chat bot, to make it more accessible to precarious demographics. The people who need help the most are often the hardest to reach. Our dashboard allows ATO officials to monitor how effective Tax Help centres are and apply appropriate resources. The upgrades to Alex allow Tax Help centres to be more easily found, and also feed data back into the dashboard about who needs help.
GoGoViz JNA Mobile Ballarat 7 8 *When visualisations are removed from the real world, for example when shared on FaceBook or Linked in, there's danger that they become an amusement, sometimes trivialising what could be serious and impactful content.* *In other cases information is simply hard to find when and where you need it.* GoGoViz addresses both these issue by using AR and GeoLocation technology to situate information and visualisations in the real world. There are several examples included in the video such as finding heritage locations visually and translating information about them in to one of over fifty languages available. The application also provides a unique way to enable story-telling by letting users to create, and share their their own visualisations which can then be viewed and interacted with by other users. --- **Status** Pretty much everything in the video is real and working on the device... although with plenty of hacks and bandages. Please don't judge the code quality :) Front end includes working: AR, GeoLocation, Maps and Translation. Back end includes working REST API for querying data and adding user data like comments and observations. **A Note on Git Repos** Note two git repos one for backend, one for frontend. Front-end is linked in the URL but both given here: https://bitbucket.org/jnamobile/govhack-frontend/ https://bitbucket.org/jnamobile/govhack-backend/ **Tech Used** Groovy, Grails, Gradle, Docker, Unity, ARCore, MapBox, Yandex Several example applications provide users access to information using location and visual markers. When combined with the translation feature this provides a powerful story about how data can support Australia's multi-cultural society. In create mode GoGoViz doesn't just tell a story it allows users to create and share their own stories! Watch the video to find out more! There are a number of data sources used in GoGoViz. The Backend exposes REST APIs for searching the National BOM observation data and VIC Free WIFI Point data. The FrontEnd directly access Ballarat Council data like BBQ data. Other data sets have excerpts embedded in the front end but are not exposed via backend, examples include Interest and Engagement with Science dataset and Central Highlands Art Atlas. *A full set of datasets with links, etc, is available in the GovHack portal.*
Go Now App The Uncivil Engineers Sunshine Coast (USC) 3 7 The application proposed will have a simple and easy to use design, display data to aid bike users. The goals of this application are to, Encourage cycling to improve health and well-being of locals and reduce emissions. Make travelling less stressful, and allow accessibility for all required information within one easy to use app and finally increase tourism in local areas due to the ease of trip planning. The application design will start at the home screen where users will be able to use the search bar to find a destination. Once the location is set specific Cloud cover provided by the Bureau of Meteorology will be transparent, showing users an initial overview of the area to decide whether they want to travel by car should the weather be too bad. Then the user will be able to select their travel route with information related to Flooding, congestion, roadworks, and other special events being shown on the map trough data from QLDTraffic GeoJSON. Since our primary focus is on encouraging bike travel, data from the Principle Cycle Network will provide cycle pathways as well as travel time. For those wishing to track their exercise goals, average calories burned for the selected cycle route will be calculated and clearly displayed within the application screen. Bubblers, taps and other public water features will also be displayed along their route and are accessed from the Sunshine Coast Council for the local area. The data used in the project serves two primary transportation purposes, car and other vehicle travel and cycling. The QLDtraffic, QLDweather and air pollution datasets displayed in a user friendly fashion on the app assists the app user in deciding whether to use the bike or car for travelling. Whereas, the cycle network, drinking fountain and national maps datasets working in tandem conveniently assists the app user in planning their cycling route.
GovCMS Data Visualisation Team Marika Sydney 2 2 Our team (of four first-time GovHackers) is interested in using opensource tools to work with open data. For this challenge we installed Drupal 8 GovCMS on a free cloud hosting site provided by Microsoft Azure. The DVF (Data Visualisation Framework) module was then installed and tested. The team then explored various features and functions of the DVF to represent numerical data in various graphs and displayed them on the website. Feedback and suggestions were then submitted on the website also. We cleaned the original dataset from (lmip.gov.au) on Occupational Projections, converted into csv format and explored the various graphical options in the Data Visualisation Framework. The size of the dataset is also reduced to a minimum. The aim is not to analyse the data but to explore how numbers are presented using the DVF module.
GovHack Team Test Project GovHack Team Test Project Brisbane 3 2 ![GovHack Logo](https://2018.hackerspace.govhack.org/assets/bannerlogo-ab7eef11d2ba1db01308a41598c4ceba43c997bb7f855f7c914dd62599980dbc.png) # Hello * hello * test Hello Hello Hello Test
GovLeave Healthy Australia Gold Coast 5 4 #Healthy Australia ###Who we are *** A team of five men with a passion... a dream... a hope to build a better connected, healthier Australia! ###What is GovLeave? *** A government managed platform to mediate the negotiation of sick leave between employers and employees in a fair and transparent manner. This platform will act as a 3rd party which sits between the employer and employee. An employee will initiate sick leave through this platform, which will in turn inform the employer of the request. Both parties will be informed of their rights and responsibilities regarding sick leave specific to the nature of their working relationship. &nbsp; Parties have the option of negotiating sick leave, and escalating issues to relevant government bodies (eg. fair work australia). This app hopes to promote employees utilising their available sick leave (to prevent the spread of disease), and also to protect employers from unfair demands. &nbsp; &nbsp; This app will provide a messaging platform between employers and employees, and also present information (health statistics and financial data) relevant to the negotiation of sick leave. AI will track the utilisation of sick leave, and help identify unfair actions by either party. &nbsp; While health statistics will attempt to inform sick employees of the risks they pose to others or, on the other hand, the consequences of taking unnecessary sick leave. &nbsp;
Grants Genie Grant Gurus Canberra 4 4 Are you a business with bright ideas with the potential to leave your competitors in the dust? Bringing and testing your innovative ideas for commercialisation can be painful especially if you’re trying to capture a first to market advantage. Then, there is the actual process of discovering relevant grants and research collaboration opportunities and applying for them! What if there is a tool that can help you target the right opportunities to help your business succeed? Grants Genie is an innovative and intuitive open source tool designed to take your business’ characteristics and lifecycle status into account to provide you with the rich intelligence needed for selecting the right grants and research based assistance. By combining Grants Connect, GNAF and ACT Population data to produce business meaningful results for grant characteristics along with demographic data and industry researcher collaborators to enhance your awareness of financial assistance and collaboration opportunities. Just how easy is it to use? Grants Genie is an interactive dashboard that takes your inputs with the aid of geolocation to help your business visualise and analyse data to investigate relationships insights such as: - Understanding successful grant profiles by viewing grant data by location, category and grant agency - Determine whether your competitors received grants by drilling down into the data by location on a map and refining by the objective of the grant - Seek industry research collaboration opportunities through identifying similar research held by industry Take charge of your business opportunities today and see what Grants Genie can do for you! Story 1: I am a researcher in a University and I want to see other businesses who have received innovation grants in the same area of research that I am in for industry research collaboration opportunities (were Industry meets Academia) Story 2: I want to start a day care business in Canberra and want to see how many other people have received child care grants in the last few years and combine that with data on the young 0 - 4 year old population in those areas which have received grants to help me choose a location for my business Story 3: I am a mango farmer who has an idea for developing a new packaging process for my mangoes so I want to search for agriculture based grants to see if individual/business have received grants for similar ideas to get an idea of whether I might have a chance of getting a grant
Hacking fish Utas fisher Launceston 9 6 Tasmania has Australia's best marine resources, not only a beautiful landscape but also a variety of fish resources. Although fishing enthusiast knows where the best place for fishing, the ordinary person does not know about this kind of information. Tasmania is very popular fishing destination among us because of easy fishing. This is an untapped potential area for tourism in Tasmania. This project to use Tasmania fishery data and social media networks to promote the development of the local economy through recreational fishing. HackFishing project mainly use six datasets to display the Tasmanian fishery distribution area map data, the Tasmanian fishery block time data, and the Tasmanian weather data. And the dataset can help fishing lovers plan their fishing time and fishing areas properly.
Happy Parking! Pakers Melbourne 7 8 The Happy Parking! project aims to make the most use of the open-source data from government solving practical problems and tell stories of urban development according to historical car park data. ### Part 1 Parkers aim to create a real-time web app for end-users, helping drivers to find a vacant spot efficiently. It allows users to select the location they want to go and get them all vacant car parks in the area within 500 m and match the car park restrictions with duration they are willing to park. It has a priority rank for the matching function -- free first, within the area, outside area. If there are no vacant spots in this area, users can also use the off-street car park locations to find a car park. At the government end, the real-time parking solution can help reduce the air pollution or traffic problem that caused by circling vehicles for vacant spaces as well as reduce the time wasted in finding a vacant spot, especially in the city area. On the other hand, the visualization shows the land utilization in a more straightforward way, which supports the government to monitor and make a decision to improve quality of life. ### Part 2 In addition, the web app also provides a visualization regarding the analysis of the parking area occupancy rate based on historical data of the past years. It demonstrates the occupancy rate changes in each street with inground sensors according to their timestamps. Regarding these car park analysis data, it enables users to understand the urban planning in Melbourne and the changes in economic centres. Moreover, support the government’s urban planning decision in car parking, Remove car parks with low occupancy rate and build greenspace or improve public transportation network construction to reduce car park stress. The datasets provided by the City of Melbourne identifies the location of car park bay and vacancy in real-time told by in-ground sensor systems, which allow us to consolidate information and generate parking solutions for drivers. For historical archived data, they give a knowledge about how well the parking systems are utilized, thus, the government could benefit from them to make a decision in respect to city resources planning. we judged the occupancy rate on the peak hour(6:30-9: 00 am & 3:00-18: 30 pm) and whether it is the weekdays and weekends to make a comparison for each car par zone.
Having a go First Timers Canberra 7 9 GovHack 2018 ·       Intro and overview o   A high performing cross functional taskforce including members from Accenture, sass, and Cloudera has been assembled to aid the government in better understanding the problem of insolvency in Australia. Insolvency costs the Australian economy in excess of $5b per year.  More specifically this hurts the individuals filing for insolvency, their employees, and the trading partners with outstanding accounts.  o   The scenario o   The task ·       Why do we care o   The cost to the economy o   The cost to owners o   The fallout to employees, trading partners and the broader community For the latest updates on the Microsoft Outlook and O365 issues, go to     Intro and overview o   A high performing cross functional taskforce including members from Accenture, sass, and Cloudera has been assembled to aid the government in better understanding the problem of insolvency in Australia. Insolvency costs the Australian economy in excess of $5b per year.  More specifically this hurts the individuals filing for insolvency, their employees, and the trading partners with outstanding accounts.  o   The scenario o   The task ·       Why do we care o   The cost to the economy o   The cost to owners o   The fallout to employees, trading partners and the broader community [‎9/‎09/‎2018 5:00 PM] Briskey, Benjamin: No Title ·       The approach o   Data from Australian Financial Security Authority vis data.gov.au o   Scraped population data from ABS o   Combined data on SA3 levels o   Developed machine learning algorithm to predict insolvency risk factors ·       The results o   Visualisation developed to understand trends and patterns in data o   QLD has highest insolvency rates by population o   Top 3 areas are Surfers Paradise, Robina, Noosa o   Correlation of 24.7% between number of insolvent businesses and unemployment rate – peaking in 2016 at 29.5% o   Correlation of 14.7% between number of insolvent individuals and unemployment rate – peaking in 2016 at 21.8% o   Weak negative correlation (12.1% and 6% for businesses and individuals respectively) between median household income and insolvency.  o   Baselined machine learning model, can be developed further with additional feature engineering or hyper parameter tuning from additional datasets o   Top insolvent business region per state: Molonglo (ACT), Mount Druitt (NSW) , Casey South (VIC), Springfield- Redbank (QLD), Rockingham (WA), Playford (SA), Brighton (TAS), Palmerstone (NT) ·       Wrap up: o   Learning Experience o   Cross functional teams delivering outcomes in short term.  ·       Giving it a go foresees an Australia in which the government can accurately identify at risk individuals and businesses before they reach the financial point of return. Enabling this proactive approach will allow for early intervention, and assistance to be provided where it is needed most.
Health + Team 346 Albany 5 2 Health+ Is an application/service that is a downloadable to mobile devices, its intent is to improve the response of emergency medical services to the public, the GUI would be built so it would be easy for the user to understand and operate effectively. The layout has 5 buttons; maps, user manual, self-diagnosis, live chat and settings. The map feature activates an emergency SOS feature that is detectable via your network provider, certified people who are trained for first aid will be able to sign up and will be able to receive and respond to nearby signals. The user manual to help guide users who are unsure how to use the application, self-diagnosis is flow chart system would show users what they could do based on the symptoms that a person could potentially display, showing the various options on what to do. Live chat calls up a GP that gives advice and assistance for people who don’t have general medical knowledge. The data used for the project would be traffic digest and traffic signal sites in order to get the fastest response times for EMS and to focus on what condition of the traffic for the people who choose to respond through the application. The target audience for this product is for people who either want to help the public when in need or people who are prone to injury or have shown medical problems in the past. But is still a handy item to have for people outside of the target audience. The result of this concept could lead to potential development and decrease the rate of fatalities due to injury and disease around the globe and would make it easier to respond to emergencies and how to help people in need sooner. We are using traffic digest data and traffic signal sites data sets from the Australian Government.
Health-Hack Running on Caffeine Sunshine Coast (USC) 8 2 Our product is an app, called HealthHack, that is integrated onto a smartwatch, for example a Fitbit or Apple Watch, that monitors health parameters including heart rate, blood pressure and respiratory rates. The user’s medical profile is created in the app as well as being synchronized with their current medical profile (if available) from myGov and Medicare. The smartwatch app interface is shown in figure 2 below. This interface shows the countdown in red rotating around the circle towards the ambulance icon. Once the red bar reaches the ambulance icon, a message will be sent to emergency services along with the user’s medical profile requesting assistance. In the middle of this circle is a large cancel button, which allows the user to cancel the call if they deem themselves safe. In addition, the user can simply tap the ambulance icon in order to summon an ambulance immediately instead of waiting for the red bar to reach the icon. There is also a parent app for mobile phones, shown in figure 1, which allows the user to edit their profile, setup a medication schedule & list current medications, a health program, health tips and tricks, and a current health section which will show their health parameter readings, as well as steps taken, calories burned, and similar statistics. Detailed Description of Project - https://drive.google.com/open?id=1KxTQtP1EESySLsx56yKSERAUmqBJjM2b Response time Response time is a vital aspect of the ambulance service because in all life threatening situations a matter of minutes can be the difference between life and death. The QLD government measures response times from the moment the call is answered to the arrival of the 1st ambulance on the scene. In 2013 the average state wide response time was 16.4 minutes. In 2015 the average state wide response time jumped to 17.1 minutes. In 2013 the average response time in capital city was 14.75 minutes. In 2015 the average response time in the capital city jumped to 16 minutes. Things that impact response time - Time between accident and call to the emergency services (unknown) - Time between call made and answering (10-45 seconds) - Call length (12.66 seconds) - Travel time (16.5 minutes) Why this is important Millions of Australians have on going health issues; let’s break down the major culprit. - 4.2 million suffer from cardiovascular disease - 645 000 were diagnosed with coronary heart disease in 2015 - 472 000 with CHD had heart attacks in 2015 - 207 600 died due heart disease - CVD was the underlying cause of 29% of ALL deaths in 2015
HealthLink HealthLink Sydney 10 3 Data is not the key to the future. Data does not define success. The key to the future, what defines success, is people. We are a data integration platform tailored for the healthcare industry, standardising the way health data is shared and incentivising collaboration between hospitals, researchers, and service providers. Data integration from various data sources takes 80% of a data scientist's time. We will unlock and connect these numerous data sources (including AIHW hospital records, ABS (SA3) demographic data and geospatial data) from numerous formats into a smart format like GeoJSON. This enables users to focus on finding answers from the data; to establish new correlations, make more informed predictions for resourcing allocation, and better combat broader challenges such as antibiotic resistance and disease spread. Through this, users are incentivised to add their own data to the platform and collaborate. In our proof-of-concept, we illustrate the significant improvement achieved via data integration and the statistical analysis such as multinomial logistic regression since made possible.
Healthy Communities - Fitness and Community Portal Unafraid of the dark web Sunshine Coast (USC) 3 16 In this project we seek to create a map based website app which informs the community of fitness related events and venues in their local area. The app also provides a forum for people to meet to help support each other for mutual support. The Following Urls are all data sets which ideally upon completion could be tied into the app to facilitate locations in the map finder for this project. Additionally data could be collected and compiled from regional councils for detailing upcoming events National https://www.data.act.gov.au/Sport-and-Recreation/Fitness-Sites/h4qc-3txc https://data.gov.au/dataset/ice-skating-centres-gfyl https://data.gov.au/dataset/martial-arts-in-victoria-gfyl https://data.gov.au/dataset/swimming-pools-gfyl https://data.gov.au/dataset/gymnastics-in-victoria-gfyl https://data.gov.au/dataset/water-sports-in-victoria-gfyl https://data.gov.au/dataset/yoga-pilates-and-tai-chi-in-victoria-gfyl https://data.gov.au/dataset/personal-training-gfyl https://data.gov.au/dataset/sailing-clubs-gfyl https://data.gov.au/dataset/athletics-in-victoria-gfyl https://data.gov.au/dataset/disability-activity-gfyl https://data.gov.au/dataset/afl-in-victoria https://data.gov.au/dataset/tracks-and-trails-gfyl Local https://data.sunshinecoast.qld.gov.au/Facilities-and-Structures/Aquatic-Centres/23vb-3ngq https://data.sunshinecoast.qld.gov.au/Facilities-and-Structures/Basketball-Courts/22aa-36ce https://data.sunshinecoast.qld.gov.au/Facilities-and-Structures/Parks-List/u7w3-88wx
Historial Mirror Team Strawberry Brisbane 7 1 Australia’s history should be acknowledged and remembered, it can inspire a nation, educate next generation, also let travelers, immigrants better understand the background of Australia. In order to engage people with ANZAC, we designed a website let our next generation, immigrants, travelers to read and understand the detailed stories behand each Anzac soldier during the First World War. Just need a click of the soldier’s photo, our website will tell you the soldier’s life experience by timeline. So, you can see their life and respect their contributions. You can also find all the ANZAC monuments in our map, we will navigate you to the monument you want to visit. Moreover, if you wish to become one of them, our website also allows you to upload your photo and we will generate your exclusive ANZAC portrait for you. Isn’t it a special souvenir? Our website provides convenient, interactive methods for next generation, immigrants and travelers to engage with ANZAC.
iBINs GovHackMyself Sunshine Coast (USC) 4 3 An interactive gps app to locate rubbish bins located near the user of the app. The app is made to be interactive and fun to use to promote an intentional focus on cleaning the environment. Features include; bin locations relative to user position, data about the use of bins, educational content, cutomisable avatars, redeemed and redeemable rewards and leaderboards. The app created is a prototype and will need more development but gives a general concept of the desired product. The data used was provided by the Sunshine Coast council and is an open data set that logs the longitude and latitude of bins on the Sunshine Coast. The data also includes the frequency of servicing which relates to the amount of use each bin receives.
Illuminating the Night Amaltr Remote VIC 5 10 The aim of this project is to look at range of data sources from Ballarat to visualise the story of life, and perceptions of safety, in our town. Right to the Night data inspired this project, as it is rich in qualitative and quantitative data. This data was mapped and compared with other features from the City of Ballarat data sets and Vic Gov data sets. These features include skate parks, bus shelters, public toilets and graffiti, amongst others. Through a visual story telling medium (and lots of maps) this project aims to share the story of challenges that Ballarat faces, and how even in a small area community experiences vary dramatically. By understanding the data and how it applies to individual experiences, government bodies can make wise decisions which can benefit everyone. In this case by making a city safer and more liveable at night. The hope of this project is to visualise data in a human way which is immediately accessible, understandable and applicable in decision making and easily communicated to the community. A number of City of Ballarat data sets and one Vic Gov dataset have been used, alongside general basemap data to create these maps and set the scene. Quotes have come directly from the Right to the Night data. BoM sunrise and sunset data was used to associate each safe/unsafe entry in the Right to the Night data with a day/night identifier.
Insolved Hard Pivot Sydney 5 4 ##Problem Statement Every year more than 30,000 Australians become insolvent, owing creditors more than 7 billion dollars. Insolvency grew 7% in the 2017-18 financial year - double the rate of bankruptcies. The reasons for insolvency are complex and varied, but impact everyone in our community. Total bankruptcy costs the Australian economy 0.5% GDP per annum. About 1,000 people per year fail to comply with their insolvency agreements, causing more distress to creditors and costing AFSA millions of dollars. ##Introducing INSOLVED Insolved is an advanced analytics engine to help everyday Australians get back on track. Using machine learning and predictive modelling, Insolved estimates with 95% accuracy if people within the personal insolvency system are at a high risk of non-compliance (for this project, we define non-compliance as Offence Referral and Objection to Discharge). ##With Insolved AFSA can: - Predict non-compliance with **95% accuracy** to take appropriate measures - **Understand trends** in insolvency and non-compliance as well as profiles of the average Australian facing insolvency - Understand **regions of financial stress in Australia** and glean insights into root causes so that **early intervention** or financial education drives can be mobilised - Understand trends for **optimal utilisation of resources** for the benefit of trustees and individuals ##Here's how it works: **Dashboard** - An AFSA employee will have a dashboard of all personal insolvency cases. - Each case shows a risk rating of High Medium or Low, based on our algorithm. - The case list can be sorted by Risk Rating, ID number or Year and filters can be applied to highlight different cases - Alternatively, employees can find a specific case by using the ID search **Prediction tool** - To predict whether someone within the personal insolvency system is at risk of non-compliance, all you have to do is fill in a few details. - Our predictive model will determine whether this person is low, medium or high risk. **Explore** We’ve compared the personal insolvency data to a variety of other datasets looking at health, housing, education and employment across Australia. We’ve found several interesting trends which can be explored within our Tableau model and are visualised in our product We found that in the top 10 geographical regions with high rates of insolvency: - Unemployment rates were 12% higher - Psychological distress rates were 17% higher - Obesity rates were 20% higher - House and unit price growth were 74% and 119% higher - The number of people with a bachelor's degree was 28% lower ... when compared to the national average. ##Roadmap _Insolved_ has the potential to drive down the cost of administration of non-compliance and reduce non-compliant debt. _But we can go further:_ - _Insolved_ could be used by the public to predict their risk of becoming insolvent and receive advice on reducing financial stress. - This information could further enable AFSA to predict trends in insolvency by location, profession, gender and family circumstances, better preparing them to deploy resources and launch education campaigns. ##Our predictive model is unique Our algorithm solves the class imbalanced or needle in haystack problem as the number of those who are non-compliant is small. We needed to come up with accurate predictions when there was an imbalanced distribution of non-compliance data within a highly skewed dataset. ##Novel and creative data insights We developed ways to correlate insolvency data and show that insolvency affects us all Australians but often affects some of the least fortunate. We did this by combining health, education, economic and housing affordability data. We also developed profiles of male and female insolvents to show insolvency affects average Australians. Check out the models/text document as we were not able to visualise everything. [Data preview below](https://www.insolved.co/gov/explore) ![summary](https://s3-ap-southeast-2.amazonaws.com/bcgdv-govhack2018/dataviz-slice.png)
inSOLVEncy Dmitry's Angels Townsville 8 7 Using ML to identify which individuals will commit insolvency by creating a compliance risk model and visualizing the results. Our project inSOLVEnt takes a multifaceted approach to what is a multifaceted problem by creating not only a risk model for addressing non-compliance to personal insolvency, but visualisations and infographics addressing the common factors leading to negative insolvent outcomes. We utilised the non-compliance personal insolvency data to first identify cases of non-compliance versus compliance. We streamlined this data using other data sources such as Regional Statistics, the ATO GovHack 2018 statistics, and ANZSCO occupation and regional classifications. Once we had a clean data set we ran through tensa flows to identify a model. We tried neural networks first, which were overfitting and not generalising in our tests. We decided to simplify using linear regressions which worked well. Out of 250,000 records we misidentified 5. This is an incredible accuracy result. When training our model, we first separated all compliance and all non-compliance. Each where then randomly split using an 80% training, and 20% validation split. As non-compliance events were the minority, this method was to ensure that our training subsets were balanced. We further delved into these results by isolating Gold Coast data by utilising AS3 data sets. We retrained our model in the same method. Our validation results for the Gold Coast data was 100%. The Gold Coast data was consistent with the National model, reinforcing the robustness of our solution. We retained both models using mean absolute error, rather than mean squared error, as mean squared error amplifies outliers. Our model is able to predict non-compliance events to a high degree of accuracy. This risk model can be used by regulatory bodies to target audit and compliance services, and individuals and corporate entities to self-identify their compliance risk.
Insolvency, Facts vs Spin Altis Canberra Canberra 3 8 We trained random forest and neural network classification models to do predictive modelling on cases of insolvency non-compliance. From these models were also able to extract useful indicators for potential non-compliance. We then combined the AFSA insolvency data set with 7 other datasets to explore a range of potential additional correlations. Beginning this project, we found that it was a relatively easy task to simply mash together a few datasets and generate visualisations that suggest one thing or another. However, we realised there wasn’t necessarily an immediate basis for these claims, so we took a step back and decided to take a more scientific approach. By leveraging random forests and a deep learning algorithm based on a triple layered neural network, we were able to train our system to recognise the key correlating factors that contributed toward non-compliance prediction and potential causation factors for personal insolvency. Only once we found these correlated contributing factors, we chose linking fields associated with these factors to find relationships. We are not claiming to have found perfect causation factors for non-compliance or insolvency, but we have built a robust system to identify where potential causality could lie in order to assist with identifying venues for further research. 
Insolvency Risk Profiler Insolvency Oracle Canberra 4 3 **We built an AI-based platform that uses information about an individual to quantity their relative insolvency risk.** Their relative risk is expressed as a number which indicates how many times less/more likely than average a given individual is to become insolvent. We also used this model to derive broad demographic trends in personal insolvency. Geographic insolvency trends are indicated on an interactive map which highlights SA3 regions by the expected insolvency rates. Trends relation to occupation, gender, and family composition are also visualised. # Overview We wanted to estimate, using a Bayesian AI model, the likelihood of a person becoming personally insolvent, given certain information about them. But to do this, we needed the marginal and prior distributions for each variable. Getting statistics about these variables for the general population was difficult, and some key variables had to be abandoned (e.g. assets, liability). However, a few key variables _could_ be correlated with census data. # Variables of interest The variables which were common to the given `non-compliance-in-personal-insolvencies.csv` dataset and 2016 census data are: - the SA3 of debtor - Family situation of debtor (Census dataset B25 SA3) - Sex of debtor (Census dataset B57A SA3) - Debtor occupation code (these seem to be Sub-Major Groups in the ANZCO ontology, see http://www.abs.gov.au/ANZSCO; the closest relevant dataset was B57A SA3 which used ANZSCO Major Groups # Approach Because we don't have the joint distribution of Debtor occupation and family situation, we can't do this with a single model. Instead, we'll have to construct two models: - Estimating Pr(non-compliance) given SA3, sex, and family situation - Estimating Pr(non-compliance) given SA3, sex, and debtor occupation We then need to find a way to combine these predictors to give a single number. Adding in quadrature after normalising by the non-compliant marginal probability seemed to be a sensible option. So we calculated the average expected risk of non-compliance (i.e. the marginal risk of non-compliance), and expressed every prediction in units of this quantity (e.g. person X is 2.5x more likely to be non-compliant than average given their demographic information).
InSolve the Insolvable InSolve the Insolvable Rockhampton 4 2 Our product is called InSOLVE. We used machine learning and/or artificial intelligence, to predict non-compliance during personal insolvency/bankruptcy. We trained a neural network to sort through the data that we used, and was able to create a website that can showcase basic insolvency data via database lookups, but also more technical temperature matrices using Mathematica, which has been programmed via MATLAB neural network matrices. The Australian Financial Security Authority (AFSA) would find this information important in investigating people after they have filed for bankruptcy. Regional communities like Rockhampton can improve their economic resilience through using Artificial Intelligence like Neural Networks to make sure that integrity is kept. While it is not illegal to go into bankruptcy itself, not complying with insolvency orders afterwards is an issue. Rockhampton and Yeppoon can improve a lot by making sure that at risk members of their community can get the extra help that they need, and the indices that we calculated can help do this ahead of time. Try putting in your details and see if you are at risk of non-compliance in the case you ever become bankrupt? We found common triggers among non-compliant records, for example location, job, family status were all variables. In the bankruptcy dataset, the criteria that we looked at was; *Calendar Year of Insolvency *SA3 Code of Debtor *Sex of Debtor Code *Single/Couple *Dependants *Debtor Occupation Code (ANZSCO) *Cause for Bankruptcy *Business Related Insolvency Code *Debtor Income Level *Primary Income Source Data *Unsecured Debts Levels Value of Assets Levels Using data from Australian Financial Security Authority (AFSA), we sought out to see if there were common triggers in these cases. For example, those who are living in Rockhampton who are single & without dependants are a large group of insolvencies, while those who are living in Rockhampton while being a couple and having dependants are more likely to not comply with their insolvency notices compared to others in Rockhampton. We have compared census data from the 2016 ABS dataset which includes Rockhampton's populations with respect to age and sex. We utilised MATLAB packages trained a neural network using our datasets, then the resultant code was implemented in Mathematica.
Insolvit Team insolvit Melbourne 6 2 Over 110,000 people in Australia are bankrupt. Whether they share it or not, each one of us knows someone who has been affected…Life doesn’t always go to plan. So we pulled together a team of data scientists, lawyers, coders and engineers to research the problem and create a solution which we call INSOLVIT - a platform that uses real data to predict the likelihood of non-compliance with these obligations, and target resources to the people who need it most. The platform has 3 main features. The compliance dashboard provides an overview of the state of non-compliance in Australia. Our heat map visualises past non-compliance based on locations. We can then overlay other data sets to find correlations and determine why certain areas have high non-compliance. In addition, our cutting edge machine learning model allowed us to find the key attributes that lead to non-compliance. By understanding WHY people are non-compliant, the government can design the right intervention, which best utilises public resources. The second feature is individual risk profiles. The Australian Financial Securities Authority (also known as AFSA) is the trustee and is responsible for around 80% of insolvent individuals. Our machine learning model allows AFSA to calculate the risk of an individual becoming non-compliant with 98% precision. Our third feature is Insolvit Together – a platform clients going through the insolvency process which promotes education and compliance. We also created a community hub. We used the AFSA Non-compliance in personal insolvencies dataset (https://data.gov.au/dataset/non-compliance-personal-insolvencies ) as the primary dataset underpinning our project. The dataset was analysed through machine learning and through a deep dive manual analysis to identify trends, curation needs, and potential for linkages with other datasets. A key limitation of this dataset was the use of SA3 for location without access to other SA codes or postcodes data. More robust linkage would improve the project. Another key limitation was the size of the relevant dataset – the number of non-compliance entries was less than a statistically significant sample, which limited the ability to correlate trends – though we were able to identify general trends. We also used the GovHackATO dataset (https://data.gov.au/dataset/govhackato ) at a greater level of location granularity to compare macroeconomic and ABS (eg: SIEFA) data as an overlay to the AFSA Non-compliance dataset. A number of other datasets were evaluated for linkage (eg: Victorian Government unemployment data from budget information, Australian Government budget information). However, again those datasets contain information at a whole of country or state level, which limits their usefulness at identifying trends with the AFSA data.
IP-identity Blockheads Canberra 5 1 # IP-identity **Can we construct a clean, fault-tolerent, distributed, borderless, IP ledger?** Yes we can! But wait, there\'s more! This decentralized database inherently will not allow duplicates. Such an application is mathematically invalid and will not succeed. With blockchain, we have solved the issue of duplication transparently and provided added benefits too. In addition, we have implemented a persistance layer between the blockchain and the user that allows the ability for any user to retrieve blockchain verified IP records from the their web browser. ## Our solution We will implement de-duplication and checking functionality using ```Levenshtein Distance``` to quantify string simmilarity and providing an expert driven interface to check the results. Our blockchain solution will be a smartcontract implemented on the EOSIO platform. Our aim is to provide a platform for internationally open and accessible IP records, where the smartcontract enforces de-duplication of records and verification. The contract will also feature user permissions such that IP agencies can audit and update records where necessary. The final key benefit that our platform offers over traditional solutions, is that it is truly *borderless*. International IP authorities and stakeholders can interact with the database in a way that is trustfree, secure, and globalised. We thought, why not decentralize the work of deduplication too? When applicants come to register, we have implemented a similarity score using the "Levenshtein Distance" to records in the existing database. Users can then make sure they select the right information. This is an expert driven solution that will not only help deduplicate data, but also assist in the migration to the blockchain.
J.A.G ImEmployable Launceston 6 4 J.A.G (Job And Growth) is a project designed around making sense of employment and higher education data. The project creates a visualisation in the form of an infographic for the viewer based on the selected State\Territory and\or industry. Our project used datasets from government databases to do with population, employment and higher education. Some of the data required some extrapolation and format conversion to enable us to correlate datasets together. In one case, we needed to create a map between the industry codes used in one table to those used in another in order to build the correlation.
Joe's Adventure Askar and Sebastian Brisbane 4 5 Joe’s Adventure is a short animation targeted at youth and children about an immigrant from the UK who comes to Australia in the late 18th / early 19th century. It is an attempt to narrativize some of the data in the Queensland State Archives, and present it in an easily digestible format for children and youths. It highlights the dynamic nature of immigration, and how it has changed over time in Queensland. Data from the Queensland State Archives, in particular "Register of immigrants, Brisbane 1885 to 1917", was analysed, and the narrative was formed from this set. Data from the ABS, and also from Department of Home Affairs, were used to collate, clean, and curate the data on immigration, place of birth, and population in Queensland, and this was used to support the story and teach the audience about our state.
KickStart-Up mbae Sydney 8 7 Entrepreneurs face an incredible amount of blockers that are pushing them away from realising their vision. They have to go through different processes to set up their business, get funding or find resources. We want to build a platform that will automate most of these tasks using Artificial Intelligence
Litter in the waterways poster Team 331 Toowoomba 1 0 This poster was created to educate children on why they should not litter as it can travel through our waterways and destroy the oceans and beaches.
Litter Race CaseyCoder Toowoomba 1 0 Make the guy throw the rubbish in the bin by pressing the space key.
Little Rubbish Data Junkies Rockhampton 3 3 Given the enormous problem of fast food packaging being littered all over Queensland, in our parks, streets, forests, waterways, beaches and oceans: this is causing enormous damage to our environment and health of our communities, as well as costing us millions of dollars in clean-up costs. Our plan is to develop a practical solution that involves using a challenging yet entertaining gamification approach to foster awareness of the importance of preventing and/or cleaning up litter among the queensland communities. Our plan is to maximise the use of data sets such as the Litter auditing data from South West Queensland Litter Prevention Pilot Project, SoE2015: Main material types littered, SoE2015: Number of litter items in Queensland, joined with local government area datasets to bring factual data into the app that represents the true extent of the problem and brings a fun gaming approach to solving the issue that is aimed at changing people’s mindset and changing the culture of littering being everybody’s problem and everybody’s responsibility. We hope this gaming solution will go a long way in educating the younger generation about the responsibility of waste removal in schools. Using a number of data sets we were able to identify Queensland’s most problematic litter areas. We downloaded a number of data files, e.g. the litter audit CSV file, loaded it into a database and counts for Fast food (takeaway) were tallied together. Bin counts were also totalled together. The data was then loaded into a mysql database where it could be queried directly. Next we created a REST api to return the litter audit data in JSON format. We then analysed this data and found highly travelled areas were the ones which had the most litter. We matched these areas to the regional councils these specific areas falls under. We identified datasets that linked state and non-state schools as well as fast food outlets that could be plotted to each specific area. Data Feeds Developed: http://54.79.121.184/api http://54.79.121.184/api/total_bins%20%3E%200%20and%20total_rubbish%20%3E%200 http://54.79.121.184/api/total_rubbish%20%3E%200/total_rubbish%20DESC
Location Data Search Locate Data Brisbane 2 3 You can search for the data in the 'Input Data' search box and the location in the 'Location Search' box. This will return all the data it has found. People can search for 'electronics store in Brisbane CBD' and find what they're looking for but searching for 'Accident Data Brisbane CBD' returns semi-relevant or irrelevant data.
Machine Learning Pengunz Albany 5 2 Hi, we are the pengunz and our project encompasses three Govhack challenges relating to the implementation of machine learning algorithms into data-sets to better achieve results. Machine learning is the use of a variety of algorithms to conduct in-depth analysis of data-sets to fit specific requests. Machine learning is effective in finding patterns in data to better understand the cause of data outcomes. To demonstrate a practical application for this we come to our first issued challenge: Helping to predict non-compliance in the personal insolvency system. We collected data from the ATO and the AFSA and used Microsoft Azure to develop methods of utilising machine learning algorithms to better use and organise the data.
Make A Move Motley Crue Perth 6 1
Make Melbourne Great Again Small Data team Melbourne 5 4 OzBusiness is a web application that provides small business owners and entrepreneurs a platform to easily find a suitable area to establish their business. Using various sources of data, OzBusiness filters out any unfitting areas for the user's particular requirements leaving behind the best options for them. https://data.melbourne.vic.gov.au/Economy/Small-Areas-for-Census-of-Land-Use-and-Employment-/gei8-3w86 https://data.melbourne.vic.gov.au/Economy/Cafe-restaurant-bistro-seats-2017/dyqx-cfn5 http://www.pedestrian.melbourne.vic.gov.au/ https://data.melbourne.vic.gov.au/Property-Planning/City-of-Melbourne-Population-Forecast/knxm-mrvh https://data.melbourne.vic.gov.au/Economy/Employment-and-floor-space-forecasts-by-urban-rene/rsje-n6de
Map it your Way! Engine C6 Adelaide 4 4 A toolchain to produce customised maps for loading into a Garmin GPS for specialised uses. An example is provided for the CFS to use as a replacement/supplement to existing Emergency Services Map Book and Group Response Plans. 8 OpenStreetMap is the core data providing the basemap (Worldwide) that allows routing, town names, address lookup and so on * Relevant (public) data is incorporated into OpenStreetMap (or simply validated) * Private data is mapped and saved locally * A script is then run to download the wanted area from OpenStreetMap and transform it into the desired "look" using customised styling rules.
Marauders App Codefefe Melbourne 8 5 Melbourne's population is growing with a bold prediction to surpass 5 million by 2021 and past 8 million by 2050. The focus is currently on transport systems such as rail and road, but what about foot traffic? <br> The Marauders App is a crowd-sourced application that connects everyday explorers together. <br> The Marauders App is an interactive map where explorers can create alerts for disruptive events like footpath closures due to nearby construction or social events like street festivals. <br> By using the Marauders App, you can choose to avoid foot traffic if you're in a rush or embrace the path with the most foot traffic to feel safer walking home late at night. Explorers can also quickly search for nearby public facilities at the end of their fingertips and give ratings to share their experiences with fellow explorers! <br> Not only will explorers benefit but Government bodies can use the Marauders App to: - Alert explorers ahead of time of potential events and ease or divert the congestion of foot traffic. - Send emergency response teams to respond to accidents alerted by explorers - Using the ratings given by explorers, Government bodies can easily determine where funding should be allocated to further improve public facilities. <br> Being connected and feeling safe has never been easier. The possibilities are endless with the Marauders App! The City of Melbourne has provided us with many geolocation based data sets of the city's various facilities, amenities, structures, and artwork. Our app allows these data to be shown in one central and convenient application. This enriches the explorer's experience and enables them to better tour our city. Additionally, users can provide feedback and reviews through the app itself. This crowdsourced data can help the government improve decision making and help them to target issues that people are voicing by providing them a mechanism to communicate back to the government.
Markdown SeniorSavers Rockhampton 4 3 Markdown is our project which is both an open api platform and a proof of concept application built on this platform. **SSApi Open Data Platform** SSApi is an open data platform built using existing open data sets. It allows any organisation or individual to query for senior and companion card holder discounts offered by Australian businesses. This platform aims to be a national centralized and open platform for storing business discount services. We provide a number of APIS that allow you to discover businesses near your location, different categories or services and what discounts are available. **Markdown** Markdown is a proof of concept application that provides a way for senior and companion card holders to find local Businesses offering discounted services. You simple select a category you are interested in and it will show all discounted services, promoting businesses within walking distance and showing the walking time to the business. **SSApi Open Data Platform** We discovered that while Australian states and territories are currently capturing a large amount of discount datasets this data is not easily accessible and is sometimes missing key information. This prevents senior and companion card holders from accessing this information and causes an inconsistency with the how it is provided. We extracted different business discount datasets, cleaned them, processed them, and combined them in order to produce a single clean dataset. While it isn't perfect it is now in a format that we can service from a central location and in a consistent format. We built an api backend that is freely available. It allows any organisation to query what discount services are available, searching by location, and categories. This promotes open data as this information is accessible to anyone and ensures that all discount services can be located in a central source for all Australian states and territories. **Our Application and use case of this data** We have build a proof of concept front end application called Markdown, this application takes the user's geolocation data using this to display all discount services nearby. It then promotes to the user the locations within walking distance, enticing them to walk.
Melbourne: Now and Then Team 106 Wyndham 1 2 Melbourne: Now and Then displays images of key landmarks in our city in two states, past and present. Surrounding the imagery, is data displaying the future of the surrounding building environment. People largely enjoy looking at old photos, but it's difficult to gain context as to where they were taken, when they were taken, what the location looks like today, and what is changing in the future. It's difficult to see a photo on the internet, whether it's through News or Social Media, and trace down the source and then go and find the physical location and details about the surrounding future. Melbourne: Now and Then alleviates that issue. Having an easy way to explore Melbourne through imagery and interactive maps helps the user build on their knowledge of the ever changing landscape.
micents micents Melbourne 4 0 There is a need to improve government and residents interactions to have a both way communication. There are many data collection points for government data but still there is no dedicated social network platform for government-residents interaction and decision making For example, if Kensignton, Vic city wants to open a new school and wants to have interaction with residents of that city then there is no dedicated channel for that. Kensington, Vic city may post it on their website and may ask for suggestions but not many residents go and check Kensington, Vic city website. I propose to have decision making more interactive by posting questions on social network to residents like http://www.micents.com/polls/view/4/location-of-a-school-in Such page gives an opportunity to every resident to be part of the decision making even for small decisions. Recent changes in social network data privacy has made it tough for social networks to share data or analysis of such polls with government. Web Scraping of web page is one way but better solution is to have a dedicated social network for Australian government to interact with residents. For data privacy, this social network should be deployed on government servers and data will be owned by government. The page mentioned above is deployed on the site owned by me. I own the domain name as well the code of this site. micents can build this solution for government at almost no cost. Government will own the data as it will be deployed on government servers
Migration Blues Migration Blues Launceston 8 2 The Migration Blues project aims to convert Australian Bureau of Statistics data into a visual and audio format, i.e. to represent numbers by color and notes. Senses were developed earlier than analytical abilities during the evolution process. As such, the communication with humans via senses is more productive than through the logic. Music and colors are synchronised, i.e. the solution affects two human perception channels - sight and hearing producing the sinergetic outcome. Welcome to the Migration Blues project for the 2018 GovHack competition. The team is based in Lauceston and worked out of the Enterprize Startup space. Our project is about representing data in an audible and visual format. This project took data from the ABS, namely interstate migration data and then apply some programming algorithms to convert that data into music. This was combined with some backing music that was composed especially for the event to create a different type of experience. The music has been uploaded to our website. The website responds visually to the music to create a multi-sensory experince of the data. Now we no longer have to waide through columns of number we can EXPERIENCE the data. The original dataset we take from http://stat.data.abs.gov.au/ “Interstate Migration by States and Territories of Arrival and Departure by Sex” is our key dataset. In addition, we used Colonial Tasmanian Family Links database the to acknowledge the respect to original newcomers to Tasmania (http://portal.archives.tas.gov.au/menu.aspx?search=8).
MyAustralia The Outsiders Wyndham 6 5 This project aims to reduce misconceptions about migrant groups in the age of social media by letting communities tell their stories complemented by facts. Our website provides a platform for fact checkers to provide sound facts in response to stories highlighted by users. Some assertions made in the media about social facts can easily be checked by our fact checkers by constructing a query on the right datasets from trusted sources such as AIHW, data.vic and ABS. We provide a plain English explanation of what the query shows, show a visualisation (chart or graph) where appropriate, and name the data source.
MyBiz MyBiz Melbourne 2 2 Help small business establish or extend their business Local cafe owner would like to open a new business opportunity - children party service based on a successful existing business venue. The cafe owner would like to know the demographic and competitor data to decide whether they should invest in this idea. They are not technical savvy, therefore an easy to use application with a friendly user interface would help them to put all their questions together and reach the answer.
MyCity B&C Canberra 6 4 #Watch our entry video [Click here to watch our entry video](https://drive.google.com/file/d/1croDbkCD4-CM5u3EXbcMFOqKz8f29_nc/view) ![alt text](https://media.giphy.com/media/deyTNzeBkIjaIFjLM7/giphy.gif "MyCity") ___ ## The Problem: According to Australian Institute of Health and Welfare, almost two-thirds of Australian adults are overweight, and less than half get the recommended 30 minutes of moderate intensity physical activity on most days (AIHW). Furthermore, over 40% of Australians do not feel connected to their community (NAB’s Q1 2016 Wellbeing Index). ## Our Goal: To make Australians healthier, more active, and more connected to their local community. ##How?: MyCity is a gamified augmented-reality mobile application that offers incentives for people to be active and involved in their local community. The user is given points for travelling to a point-of-interest and playing short interactive Augmented-Reality games. The aim is to compete with friends in teams to get the most points and top the leader-boards. MyCity is designed to promote exploration and a connection to the community. MyCity can also accurately track the health of users and compare their health to data from the Australian Institute of Health and Welfare. This allows the user to accurately see how their health compares to national and local averages, as well as across different population groups. For example, the user can see how their health ranks against other indigenous women in the local area. Making users aware of how their health compares to others is an essential tool in ensuring communities are healthy and strong. ___ “Those who feel more connected within their local communities typically have higher levels of personal wellbeing.” – NAB Group Chief Economist, NAB’s Q1 2016 Wellbeing Index. Project MyCity is dependent on open government data. Geospatial data from the Australian Capital Territory is used extensively. This includes aerial imagery and points-of-interest such as the locations of fitness sites and public sculptures and art. The aim of MyCity is to promote exploration and physical activity in the user’s local area, which will increase their overall health. This is done by offering incentives to the user for visiting and interacting with the points-of-interest. While the user is using the MyCity app, data is gathered about their fitness activity. This data, combined with the user’s personal info, is then compared to open data provided by the Australian Institute of Health and Welfare. This allows the user to accurately see how their health compares to national and local averages, as well as across different population groups. For example, the user can see how their health ranks against other indigenous women in the local area. This project is a demo which uses geospatial data from the Australian Capital Territory only. However, with the increasing availability of open-government data, MyCity can easily be expanded to include a wider range of data from more areas across Australia. Open government data is essential to building healthier and stronger communities.
MyGov Connect Greatest Hits of of '89 & '91 Melbourne 5 11 An expanded concept of the MyGov platform. MyGov Connect, would promote users to engage in government and local council endorsed services. These services would be provided with an accreditation to inform users of this endorsement. Furthermore, use of these services will users to accrue loyalty points. Which can be either used as a discount for other MyGov Connect supported Services or put into a community points pool. The end receiver of these points are dependent on the user's local area, which service requires most attention and a eligibility criteria set by Centrelink. The overall aim of this platform is create healthier and more connected communities. This would also provide a final wellness indicator for a particular community. Furthermore, to expand the existing MyGov platform and push government services that are relevant and optimized to the user. The data sets used focus on local council data and their facilities such as libraries and kindergartens. As well, as ATO data sets on Tax Help centers and City of Melbourne data, in regards to support services. These open data sets are aggregated to provide users a clear picture of the facilities and services available to them.
My Local School My Local School Wyndham 2 3 *Smarter school zones for connected communities* **My Local School** uses open data and open source software to generate alternative school intake zones. These zones are cohesive community regions that take into account the freeways, busy roads, railway lines and other barriers to travel. Households within these zones have the certainty that their assigned school is the shortest travel distance for their neighbourhood. **My Local School** uses these open datasets: * [ABS Mesh Blocks and Statistical Areas](https://data.gov.au/dataset/psma-administrative-boundaries/resource/e350fd4f-c589-4804-a4e7-a1ead4987514) * [Local Government Areas](https://data.gov.au/dataset/psma-administrative-boundaries/resource/827752c4-a75e-4f86-9540-3bb96684e856) * [Wyndham Subdivision Stage Boundaries](https://www.data.gov.au/dataset/wyndham-city-subdivision-stage-boundaries) * [Victorian Department of Education and Training](https://www.data.vic.gov.au/data/dataset/school-locations-2018) * [Melbourne School Zones](http://melbourneschoolzones.com) * [OpenStreetMap](https://overpass-api.de/index.html) The PSMA and Wyndham geographic datasets represent small neighbourhood units that, combined with routing OpenStreetMap analysis, generate cohesive community regions for fairer school intake zones.
My local story Team 101 Melbourne 5 9 A local story generator for kids to put together a story board similar to a comic book. The style chosen is a "choose your own adventure" but the adventure is links to various data sources linked on many dimensions. With the diverse data available, every story created is different. The story can then be shared with friends and family. The story is backed by data which is also credited. A unique way to bring various data sources together. Sharing promotes the importance of open data in our community. This also uses a higher order learning by not telling, not showing but actually allowing users to create and share. Thereby we ingrain in our future generations the importance of data, data sharing and how data is linked across various facets of our lives. There are a lot of open data sources but in many cases they are hard to link meaningfully. In our case we took to some data munging to find plausible dimensions in the data to allow linking. Things like geo location of school locations and sports complexes was simple. An extension was gender across things like crime stats, teacher/student data and job markets. We took some deep dives in linking location to language spoken from data such as the community profiles data. This created a framework for likely segues that a creator of a story book may take. The rest is left up to the user to choose their own adventure and bring together their own data backed story.
My MP Zero c00l Melbourne 8 2 Imagine if your politicians were more data driven. Imagine if you could make sure your needs and your preferences were right there in front of your MP so every decision they made were backed by facts and evidence instead of being influenced by lobbyists and personal biases. This app puts your needs in the middle of the political process. Welcome to My MP. We believe that politicians don't like dirty business any more than we do. So we want to provide them the evidence they need to be able to tell friend from foe. We understand these are busy people, constantly having to make quick decisions and think on their feet. My MP is the information superweapon that will give the truth a fighting chance. There are two main interfaces to My MP, the MP dashboard and the citizen view. The MP dashboard is like Wikipedia, only better. By adoping a standard information template, every topic or question is presented in a familiar and easy-to-read format, linked directly to the demographics of their area of responsibility. The relationship between a topic or issue and the people in their constituency is displayed as a summary for them to refer to. With this kind of quick information display, we are raising the bar on anyone trying to "pull a swifty" with sweeping statements and generalisations. They also get a view into the concerns and interests of the people living in their electorates so that they are always connected to the current needs of the people. The citizen dashboard is a way for individuals to safely and anonymously interact with their MP. My MP allows politicians to engage more effectively with the people of Australia while keeping their eye on the big picture. The citizen dashboard includes based information about your local member of parliament so people will always be able to know who is representing them, and what they are currently engaged in. The current activity of the MP is shown in a simplified display which allows people to discover new information about current activities. MPs can put our polls, surveys or general questions when they would like to get rapid feedback on the views of their electorate. Let's look at how this will contribute to the challenges laid down at GovHack and the datasets presented. Consider how valuable it would be to make sure that the data from your organisation or department made its way directly into the hands of key decision makers at just the right time. Rather than focusing on implementation of the technology, I have chosen to highlight how powerful this kind of information summary can be. Nothing is more important than empowering a decision-maker in the moment they are making a choice, and that is really the story to tell here.
My Two Cents Fighting Mongooses Sydney 4 4 My Two Cents is about you having the voice to be heard and enabling others to do the same. Have you ever had an issue with a local service but no where to turn? Some people do not know off the top of their head which council or department manages services, we want to change that. With My Two Cents, you will be able to make geolocated complaints, view other peoples complaints, discuss and bring attention to these problems. Most importantly, you will be heard. My Two Cents will colate every issue nationwide, and notify every department available. If a bus stop is experiencing trouble, then your council, your electorate and even the department of transport will hear about this. We will bring attention to popular issues in the community and empower individuals. Through using Map data we hope to achieve a more connected community by allowing everyone's voices to be heard
New age Business 0pt1c N3t Mount Gambier 10 8 An application for people on how to create or grow their small business at easy and stress free. We have used these data-sets because they are relevant the project. Our prototype application will manipulate them to suite the user and display relevant information. For example; using the following data-set (https://www.data.brisbane.qld.gov.au/data/dataset/26764a23-f2cf-4272-b755-04c494b157db), the application can find nearby stores in Brisbane with all the details required. The data-set is dynamic, meaning it updates constantly as it is changed.
#NewAustraliaDay NT BBQ Movement Alice Springs 4 0 G'day Australia, Welcome to the #NewAustraliaDay project! #NewAustraliaDay is an openculture, opensource and opendata initiative that believes Australia needs to resolve some fundamental issues with our current democratic identity in order to grow into a prosperous, forward looking nation. It's early days for the #NewAustraliaDay project, but we're pleased be participating in Govhack 2018 for the first time and are really starting to think about how a #NewAustraliaDay might contibute to solving some of the big data and  governance matters of our times. As part of the GovHack event we've made some big fixes to the website and general messaging. We've also setup some space for a #NewAustraliaDay data policy here. Check it out! Huge respect to all the amazing GovHackers across Australia that are making great open source projects and contributing to a better world! #NewAustraliaDay team In order to get started with a practical example of how we can use open data effectively and meet the terms of the GovHack data usage and competition elements, we've implemented a BBQ Finder service. Check it out! Our Rationale? BBQs have always played an important part in serious Australian cultural movements! Example datasets we are using: http://open-darwin.opendata.arcgis.com/datasets/barbeques   (NT) https://www.data.act.gov.au/Infrastructure-and-Utilities/Public-Barbeques-in-the-ACT/n3b4-mm52 (ACT) We've also started to implement some visualisations of the movement towards change.
NFCup Bridge Builders Guide To The Galaxy Mount Gambier 4 3 The NFCup is a revolutionary device that forces drivers to put their phones away removing the threat of mobile distraction. It is linked to your drivers license allowing for you to check The data we used for our project was to help justify why we need this product.
NoosaHydro NoosaHydro Sunshine Coast (Peregian Digital Hub) 6 1 We used BOM and Noosa Council datasets to perform a rough feasibility study for generating Noosa Electricity needs using the East Australian Current and modern hydro barges. This years govhack carries 2 different challenges urging us to use ocean data, which got us thinking We've all seen the movie Nemo, where they catch the East Australian Current for a free trip to Sydney. Well - turns out that's actually a real thing. Messing with the BOM dataset, we found that the fastest and most concentrated point of this current comes right up to our coast at the chokepoint formed by Noosa headland. The worlds first ocean electricity megagenerator has just completed its first year of operations. 24 hours a day it generates continuous emissions free electricity. It manages a whopping 3 gigwatt hours annually from one single barge. We wondered - can we use the Bureau of Meteorology dataset and Noosa Council resources to calculate a preliminary feasibility study? Where is the ideal point to moor a barge to best capture this free energy? What's the scale of a turbine that would be needed to best capture this energy, given the flow rates indicated from this data? And How many barges would be needed to supply the entirety of Noosa's energy needs? So we spent Friday and Saturday perusing the available data, searching out the electricity consumption figures for Noosa, and locating comparative efficiency measurements for hydro generation. Finding the ocean dataset and decoding the nc format it's delivered in turned out to be somewhat problematic, as was the license restrictions for the underlying master measurements, which come in at more than 7 terabytes of compressed readings going back over 20 years, but we managed to find a pre-computed visualisation with location and current-scale readings which is very suitable. This is a hackthon after all: we don't have time to grab the whole set and run a multi-decade analysis in just one weekend; but the data IS there so if our idea moves to a full feasibility study, everything needed to do this more accurately is readily available. We spent Sunday buried in Microsoft Excel putting the maths together, and here's what we worked out: Basing our math on hydrodynamic performance of marine hydrofoils, we computed that a 4000 meter span would be needed, placed 2 kilometers offshore from Noosa Heads, to supply Noosa's entire electricity needs. Obviously, 4000 meters is too long to be practical, however, If a barge is constructed which makes use of a pair of 100-meter-long underwater paddlewheel style generators with articulated airfoil style blades, and if a string of barges are anchored to the seabed, a mere 20 barges in this string would be sufficient to meet this demand. Mechanically Articulated blades allow for generation to stop instantly, so whale and dolphin detectors can be added to ensure no risk to sea life. We discovered that the BOM dataset indicates that it is feasible for a Noosa-based green-energy business to manufacture and operate an offshore hydroelectic facility to farm the oceans power to meet all of Noosas energy needs. I hope you like our work! If we're lucky enough to win a prize this weekend, we plan to use the money exploring this idea and possible commercialisation further.
Notice Always O(n) Canberra 4 7 Our vision is to bring communities closer together by providing a common digital space that community members can use to organise events around public spaces. When jumping on the notice website, a user can sign up or log into an exisiting account to post new cards, or they can use the map to browse current cards for their selected suburb. Before creating an event the user will be prompted to confirm that the current suburb is indeed the one they want to create the event for The user can then create an event by providing a title for their event, and a brief description of the event. A photo can also be included to provide additional context. In the future, users will create local events by clicking on a piece of public infrastructure such as a local park or barbecue. Users can browse the noticeboard for their suburb and see events made by others or view other cards such as local road closures posted by a council ACT public infrastructure locations, for tagging notices with locations.
nSPAM Team MCA Casey 2 11 **Waste management** is a critical problem facing the councils, cities and the entire country. Landfills are getting filled up and there is lot of raising concern about opening up new landfills, especially as China is closing taking up waste. Talk of more *non-biodegradable* waste (like plastics) and we are just getting started on the topic! With population increasing rapidly and council resident rates going up, the problem is only expected to increase in magnitude. Governments are thinking hard about this and councils have lot of initiatives to address and educate the community on this critical problem. Is there a way to better manage this using data analytics and technology? Yes!! The key priorities are: - **Educate** - Collate data across agencies, perform data analytics and machine learning to effectively identify and educate based on demographics - **Engage** - Use gamification and rewards / incentives to engage residents on reducing, segregating and avoiding waste - **Measure** - Dynamically measure waste generation to monitor and reward improved waste management practices from residents
OneGov - ID Go Go GovHackers - OneGov Melbourne 2 0 Current government records are stored across many different legacy systems which don't talk together. This means that Federal, State and Local data may be misrepresented or inaccessible. OneGov ID is a responsive web app that allows you to interact with a number of different digital government services/ IoT. It utilises the latest technologies including Blockchain to ensure validation and security of the data. Our solution is a collection of government databases, matching records, such as vehicles, land titles, patents or businesses to their associated entities. Data would be integrated from sources like the Australian Business Registry, IPAustralia, myGov, MyHealthRecord, State vehicle registries and other government databases. Access of this data would be provisioned to relevant government agencies and individuals could view their own DigitalID data on their mobile device through biometric authentication.
OneGov - IP Go Go GovHackers - IP Melbourne 5 1 As IP applicants are inconsistent with providing their details, IP Australia have duplicated records and misidentified businesses Our solution OneGov is an intuitive search system that integrates from sources IPAustralia. The search engine has been designed using natural language, guiding the user to find and filter their search easily.We use a controlled decentralised blockchain to help securely deliver complete records that are verified and up to date. We used the IP data as we wanted to solve the problem of data-matching, duplication and verification. In addition to making it easy and seamless to use.
Open Data portal Nobody Darwin 6 3 Data portal with better API and data format support Any dataset from Trello NT data box. Health Budget expenditure database used for data trail for API server
Orana Welcome Home TubeLights Melbourne 10 8 Orana is an interactive website that can recommend migrants which suburb to move to, by exploring and understanding Government and open data about various Victorian suburbs. Orana provides insights on factors providing overall quality of life in selected suburbs and provides an avenue for exploring the multi-cultural diversity of Australia. Migrants sea change into Victoria will have well-informed data-driven insights to help them relocate or immigrate. Orana originally came from First People of Australia Wiradjuri language meaning "welcome". Embrace multiculturalism! Data inquiries include: Do immigrants lives longer than people who were born locally? What are the factors impacting quality of lifes? Why does one suburb tend to have a higher number of healthier and happier people than others? Does community belonging have significant impact on an immigrant well-being? E.g. Will Italian immigrant be happier living in Carlton when there are plenty of Italian food and strong Italian community? Will factors like income and education level play a role in age longevity?
Our Envrionmental Impact IWasTheOnlyYouth Wyndham 2 3 # Our Environmental Impact ![Our Environmental Impact Logo](https://cdn.rawgit.com/edwr/Our-Environmental-Impact/dc8f7514/src/icon.png) A project for Govhack 2018 that analyses the impact we have on the environment using open data to help aid in decision making. Wyndham Tree And Latest Inspection Data is used to monitor the health of trees in the environment to estimate the health of the ecosystem. The National Pollutant Inventory is used to identify causes of CO2 emissions and pollution. The Wyndham Solar Energy Production daily dataset is used to monitor the use of solar energy and the CO2 emissions that have been prevented by using solar energy.
Our Place The Casuals Brisbane 10 0 Our Place is a virtual mural that has been created with data collated from various data sets. The aim is to create a reflection of individual community issues such as homelessness, littering, air pollution and even the possibility of disasters and the communities resilience can be displayed. The website uses post code to search for data and show it through the display. The display was created in mind of using billboards around the cities and communities to promote knowledge of issues and raise awareness. The website fetches the live data feed to make sure the project is constantly up to date so that the community can see the changes they make. NOTE: We focused on mashing up multiple data sets and the assets to display those metrics to showcase our vision, over getting the proof of concept website working end to end on a server (especially given it is an optional element and we had no funds to host a website) this resulted in the code base containing all the assets and data pooling systems required but not a polished fully functional site, shortcuts where taken. We use the number of litter items in Queensland data set to show the community the state of the issue around their community. The digital mural reflects the amount of litter through images, this is done by grabbing the litter items per 1000sqm data, we would have loved this to be broken down into smaller regions but we still feel it is relevant to each community. We use the disaster data set "Queensland resilience" to reflect how the community bounces back from natural disasters such as floods, bush fires and cyclones. The Sunny Coast data set "Community markets" is used to show when Markets are held by showing several tents on the mural. We use the science data set of air quality monitoring represented by the smog in the background of our mural. We do this by polling the live data feed. The AIHW data set is used to show homeless figures throughout the different states. This is represented by figures sleeping through the park in the mural, we struggled with this data set due to the format. The weather data set was used to make the mural more relate-able to the community, it was represented by different weather graphics.
Our Stories Jimmy and even more insignifacants Mount Gambier 6 8 The Our Stories app is a Wikipedia like app that allows people to view Australian stories. It is allowing these Australian stories to be more open and allowing them to be used by others for educational or personal use. We have used various history orientated data sets, which would be able to be used for the app to fact check the user written stories uploaded on the app. Our challenges are also based around using data in new and interesting ways to make it more open to the public.
Pay It Forward HutSix Alice Springs 8 3 Pay it Forward NT is the platform for acts of kindness in the Northern Territory.
People's Budget Tiny Happy People Hacking Canberra 8 2 <p>This project is a visualisation representing the Australian budget by the dollars flowing to different departments, representing the physical movement of dollars on a map-like inferface involving different government portfolio areas. <BR> ![The Tiny Happy People Hacking](http://i306.photobucket.com/albums/nn262/Aceyducey/623a72ef-5a2d-4a64-a807-c49cfd088acf.png) <BR> Built as both Federal government (2017-18 budget) and ACT government (2017-18 budget) visualisations,this is designed as a novel way for the public to visualise and think about the budget. <br><br> This prototype focuses on tax monies flowing into the government and being distributed to different departmental/directorate portfolios, with potential, with more time, to model the data by policy theme, or to map the full flow of money from tax income, to agencies then out to various government services and contractors. <br><br> We believe that modelling the budget in this way, moving away from graphs (which many people struggle to read), and showing 'live' flows of funding that could eventually be modelled in near-real-time, would help provide a different way for Australians and Canberrans to think about, and consider, how government accumulates and spends money within the economy. <br><br> This form of visualisation can provide new insights into where large amounts of money - or small amounts - are accumulating, and help people consider whether they feel comfortable with the government's spending choices. We used the Federal budget data for 2017-18 and the ACT budget data for 2017-2018 to create two different visualisations to visualise interactively how these budgets are allocated between different portfolios. <br><br> We did not attempt to compare the budgetary spending priorities due to the selection of a federal and state budget, however with additional time and effort we could compare different state spending priorities using departmental or thematic policy groupings such that Australians could understand the relative priorities of different Australian state and territory governments, aiding them in understanding both the differences between state needs and challenges, and the differences in policy positions across different jurisdictions (even when government has been formed by the same political party). This could similarly be done across council budgets to show the different priorities of groups of councils and identify underinvestment and overinvestment variations between them without having to look at numbers or graphs. <br><br> We believe this visualisation has enormous potential to provide a different view on Australian government spending and help people understand the priorities and choices being made - and maybe identify areas that disagree with, or that require additional public scrutiny.
Personalised Health Care Made Easy Health Hackers Remote NT 8 6 When it comes to any disorder or disability treatment, one size does not fit all. Millions of patients who will be diagnosed with any particular disorder, no two will be exactly the same plus the patients come from different background, age, gender, lifestyle, support so on which they need personalised advice to suit their lifestyle. Our project “Personalized Healthcare Made Easy” is about identifying patients who may be eligible for appropriate treatment options and activities that could help them to maintain and overcome their disorder. Any other individuals that are in risk of getting particular disorder due to the family history or other reasons could also use Personalised Healthcare Made Easy to get personalised advice re diet, exercise so on to reduce the risk.
Pikachu Team Rocket Melbourne 4 18 myCard is your one-stop solution for managing all your cards by providing you with a virtual wallet that can be accessed using your phone or an NFC card. Stats show that there are more MyKi cards in circulation that the entire population of Victoria! The number of immigrants to Australia is increasing each year. 88% of Australian are using loyalty cards. 689,000 common-wealth cards were reported lost. It can be concluded by the statistics that carrying multiple cards is an issue. Hence, myCard app will be beneficial.
Placeholder Team Placeholder Sydney 8 5 Placeholder combines multiple data sets, NSW spatial APIs, simple natural language processing and both web-based and physical visualization to help the ATO make better make decisions about where services to its more vulnerable clients should be focused in the future. For our physical visualization, see below: ![alt text](https://files.slack.com/files-pri/T070GAE1Y-FCR52NQUE/img_20180909_080448.jpg "Logo Title Text 1") Placeholder helps the ATO target their tax help program by combining the following: 1. income tax return data from the **GovhackATO dataset** to target areas with the most eligible clients i.e. low income and net capital gain areas; 2. ABS demographic data from the **GovhackATO dataset** and geo-locations of retirement villages and technical schools from **NSW spatial APIs** to target vulnerable students and seniors; 3. personal insolvency data on tax related insolvencies from the **AFSA non-compliance in personal insolvency dataset** to identify key under-served areas; and 4. flood zoning data from **SEED Environmental Planning Instrument - Flood API** to ensure that ATO's most vulnerable clients keep their heads above water - *literally*. There is clearly some existing strategies in place for centre placement, for example data showed moderate correlation between placement of centers and the numbers of retirement villages in the area. However, there was no correlation between areas with high levels of tax related personal insolvencies and the placement of the centres. This is likely due to the ATO not have access to such data and demonstrates the utility of data sharing between government departments. See below: ![alt text](https://files.slack.com/files-pri/T070GAE1Y-FCQSLF39V/pearson.png "Logo Title Text 1")
Plastic Pollution's Affect on Marine Life Data Spuds Mount Gambier 6 2 So you've heard of spuds powering computers, but have you heard of spuds coding computers? Used Data from Data.sa to primarily help marine life in the ocean. We also used a little of the unemployment rates to give a solution by giving jobs to clean up.
Presolvent Presolvent Sydney 5 3 Presolvent uses data from the Australian Financial Security Authority, in combination with ATO data to help predict when non-compliance might occur. High-risk individuals identified by Presolvent can be given additional support and guidance about managing their finances, agreeing only to appropriate debt and insolvency agreements, so they can better meet their obligations. Presolvent uses Machine Learning which is trained on limited datasets provided by the relevant Australian government bodies, it makes predictions of insolvency risk, but Presolvent is only a tool to be used in conjunction with human-assessed insolvency risk factors. We have combined a number of data sets into our application, including: - The Australian Financial Security Authorities insolvency dataset that includes over 300,000 insolvency matters to train our machine learning prediction model - ATO Tax return data set to normalise distinguish individual types from insolvent individual profile types.
Project 139 Mr A. C. G. Drake Hobart 6 1 Aggregation and tidying of the database hosted by LibrariesTas to provide a more easily usable database for future analysts. Beyond this, there is also the website (WIP) that will provide a fun and interactive way for people to learn about the voyages that came to Tasmania in the 19th Century. The data from the LibrariesTas website (accessed through data.gov.au) has over 70000 entries detailing immigration to Tasmania during the 19th Century. Due to the nature of the data being transcribe from old immigration logs, some very weathered, and no one convention between these logs, the database is very difficult to read and use in its current form. To this end, the we've converted the data to be more legible, but also computationally friendly. Aside from the JSON linked directly with the Data.Gov.Au site, there is also another list hosted by LibrariesTas that contains a list of voyages (passengers not logged) to Tasmania, which has also been analysed and a short list of ship names pulled from it. This is hoped to be used in later iterations to test outlying data points in the original dataset and tidy up errors such as incorrectly spelt names and erroneous dates.
Project 252 Team 252 Canberra 5 0 Our proposed solution touches on integrating AIHW with the broader Community health sector at State and Service Provider levels. Having noticed this to be one of the most salient problems across the community sector over the past decade, we propose a system that would facilitate community organisations as well as their funding bodies by making the MDS data formats of each state and National an open data service. It enables businesses at the service provider level gain tremendous efficiencies in how they manage data to save lives by utilising a core principle of making data more open and accessible as required. Please see Presentation252.pptx to get an overview of the solution. The folder WORK contains our 'work-in-progress' items. Streamlining the process of data capture and translation to significantly reduce costs and gain efficiencies in the healthcare sector in relation to Alcohol and Other Drug Treatment Services related Minimal Dataset.
Project 268 Team 268 Sunshine Coast (Peregian Digital Hub) 5 0 EIntroducing easyRider - More flow, less stress. A #govhack2018 submission from the Digital Hub crew in Peregian Beach to ease traffic and congestion in the Noosa shire. Our team here at the Peregian Digital Hub have entered into the local Transport & movement of people challenge using a combination of Noosa council supplied data parking capacity data and realtime sensor data from a prototype system we have developed.
Project 323 Cero Wyndham 2 0 Effective waste containment in Wyndham Waste has become a growing concern for Wyndham. We have planned to create a reward based application to contain the waste being produced in each household. This application uses an educational approach towards guiding users in being more waste conscientious.
Project 337 Team 337 Ballarat 4 9 The Right to the Night project is aimed at creating safer public spaces for women in the Ballarat CBD. Between February and May this year, The City of Ballarat and partners asked women to contribute their perspectives of safety across the CBD. During the GovHack weekend, we're investigating the data and enriching it by combining it with other open data sets from local and state goverments. We're hoping to draw some interesting connections and provide further insights into why people feel unsafe and what can be done to improve this. We looked at the perceptions of safety data collected by City of Ballarat and overlayed graffiti, CCTV, parking, trees, bollard lighting and public toilet data.
Project 342 Byte Me! Albany 2 2 - Bin It App We want to change people's behaviour - get people to put their rubbish IN THE BIN! Using our in-app reward system and coupon rewards from in-app local business sponsors, our App is also to encourage people to dispose of rubbish correctly - recyclable or not. Using the data currently available (which was sparse) for Western Australia, we have designed an App to encourage people to use a bin rather than throw their rubbish on the ground. Our App also collates and records new data regarding the type of rubbish (glass, paper, plastics etc.), where it's disposed of, and whether it's recyclable or not. 1. Researched data around municipal rubbish collection of public places. 2. Researched data re rubbish not thrown in bins & the environmental impact on flora & fauna. 3. Designed a database to hold details of bin locations, rubbish types & user profiles; and layered maps depicting bin sites of the Albany, Western Australia. 4. Designed wireframe of the App using Balsamiq. 5. Created App graphics & logos. 6. Compiled, edited and summarised all data in a video presentation.
Project 409 Team 409 Darwin 0 2
Project 4680 HackGladstone Gladstone 8 8 Community solution that reduces litter, creates healthier communities and increases regional development. How might we help prevent littering especially fast food litter and how can we help promote healthier and stronger communities around Queensland?  We reviewed the data collected and analysed to find the most appropriate course of action. Some of the information interpreted from the data were; that littering was largely going down in Australia, Queensland was the only state that had a regression in "Plastics", Although the premise largely focussed on "Fast Food" litter, we cannot find enough data to help formulate a definitive plan to address the problem. Some of the analysis we did focused on related possible reasons for the apparent deficit in improvement in Queensland. We compared the population growth, tourism rates, industry growth against the littering rates data.  Although some areas suggested a correlation, causation was not apparent.      Talking with local community caretaker from his observations when cleaning up was that cigarette butts and glassware was still a major problem, this matched the data from our analysis. We also wanted to review the data for healthier communities, when it comes to mental and social health in the community most of the data appeared representative of the most severe forms of health problems. Identifying/preventing social isolation would be a good start to address these issues before they become severe. The paramount issue we encountered was a lack of data resolution to help make clear decisions moving forward but believe this solution will be a sustainable solution. Interactive map: https://sleeples.love/govhack App prototype: https://marvelapp.com/9fdb1j7/screen/47640001
Project 67 Team 67 Brisbane 3 1 Using machine learning skills to mine useful patterns related to litter management from open data source, which can help government and relevant department to take measures. Nowadays, the amount of litters increases very fast and severely damage the environment. But deal with litters cost a huge amount of money. Therefore, to come up with a solution to this problem is becoming much more important.
Project Airscape Team Airscape Albany 8 18 Project Airscape is an application that lets you, the users, to track air pollution in Australia - and ideally find a correlation between air quality and ocean pollution. Our original idea was to create an application that would show both air pollution data, and ocean swell/current and pollution data, to see if the application could identify a correlation between the 2. Due to time constraints, the current application simply shows you the air quality data for a searched location. The application is restricted to eastern states (Queensland, ACT) due to the data available to us - however it would definitely be possible to expand this in the future. We are utilising HTML 5 speech synthesis, to make the data more accessible to people with visual impairments, and to make the interpretation of the data easier on the user. This application could be useful for people who are conscious of air quality, who are looking to move to a new location.
Project Arc The Ogrelords Rockhampton 4 1 ##Problem brief Pollution is still a prevalent issue surrounding the seas and oceans of Australia. In order to help better the protection of the ecosystem, the ability to predict major flow of waste will help maximise the efficiency of waste removal. ##Solution A forecasting engine, which allows predictions for where rubbish will end up based on currents. Alongside the forecasting engine there will be an app which allows users to report rubbish when they are out on the water. ##Who are we? We are project ARC (Australian Rubbish Cleanup). Our mission is to protect Australia's Reefs and Marine Life by removing plastic from our Oceans. Our promise is to leave a Clean and Brighter future. ##What we are going to do? Our mission is to help protect Australia’s reefs and marine life by maximising the efficiency of waste removal in our oceans. We can only do so much with code, we need the Australian community to help out and we have strong motivations backing our proposal. We will strive to encourage both young and older generations to use our mobile app, which is an easy way for the community to help contribute to the protection of our marine life and provide a healthier, cleaner environment for future generations to experience. ##What’s our vision for the future? We want future Australian generations to witness the beauty that is our marine life. Our current proposal is just the first phase of our 3-phase project. Phase 1: Our current proposal. Phase 2: Add more data to the predictive solution. Phase 3: Implementing AI to map the predictive solutions for us. ##What data have we used? The data that we found to be the most valuable to our cause and goals included three of the datasets available. These datasets include: OceanTemperatures, OceanMotionU, OceanMotionV. We have gathered the horizontal and vertical currents throughout the Tasman Sea from the motion datasets and combined the information with that of the ocean temperatures to effectively predict the movement of rubbish in the area. The information from temperature dataset was used to see if there was any correlation between the quantity of rubbish and the temperature of the water. For future aspirations, we will investigate wider datasets that cater for information all around Australia. This will inevitably include Queensland so we will be able to better cater for local communities and businesses. Another positive effect a wider dataset can provide is the ability to better determine patterns in the data. A better understanding of the current movements and properties will create a more effective and efficient app for the community to respond to. ##How does the data impact the story we are telling? Using water current data we can predict where plastic rubbish is going to be and therefore intercept using sea bins. Additionally we can use data sets to show where Australia’s pollution locations in combination with storm water drains to predict where plastic is going to be. ##See our story on Facebook https://m.facebook.com/story.php?story_fbid=10214380809326360&id=1001658455 ##Credit to Authors used in Video http://www.abc.net.au/news/2018-03-06/diver-films-wave-of-plastic-pollution-off-bali-coast/9508662 ##Our Team [Team Photo](http://54.252.244.152/img/Image.png).
Project Foothpath Immerzed Wyndham 3 10 Preparing footpath to be future ready and to automate the manual maintenance process.
Project Glad You Bot It Up Six to Fix Parramatta/ Liverpool 7 2 Everyone's life is always busy. You have to take care of your family, your finances, your jobs and relationships. The last thing you want to worry about is contacting agencies for help and find out that you have to wait on the phone line to even talk to someone to solve your issue. Our solution includes a location optimisation tool by heat mapping the traffic of government facilities, such as ATO Tax help centers, across Australia and using conversational AI to provide tailored responses to end users based on their preferences. Data Sources: 1. Gov Hack 2018 URL: https://data.gov.au/dataset/govhackato/resource/f3bcbd38-b3e9-4a27-8729-2314f05a6ae4 2. Download Austalian Postcodes URL: https://www.matthewproctor.com/australian_postcodes Technologies: 1. Jupyter Notebook 5.0.0 & Python 2.7.13 for Data Wrangling 2. Tableau 10.5.2 for Data Visualisation 3. Chatbot - Chirpy AI Chatbot Platform - https://getchirpy.ai Github Link: https://github.com/DnyaneshDesai/GovHack2018 Chatbot Links: - Individual: http://bit.ly/chirpy-individual - Volunteer: http://bit.ly/chirpy-volunteer Data Collection Spreadsheet: https://docs.google.com/spreadsheets/d/1ulH5O53HgduCizTwS4-bdxSAwHMlPgxB-VynaPRGwZI/edit?usp=sharing Github File Information: GovHack2018_Data_Wrangling_Python_Notebook.ipynb : File that contains entire data wrangling code atoabsgovhack2018.xlsx: Initial dataset file australian_postcodes.csv: Initial dataset file NSW_Data_for_Exploration.csv: Output file that contains details of 2016 tax offices NSW_Data_for_all_years_Exploration.csv: Output file that contains details of 2006,2011 & 2016 tax offices Visualization_1.twb: Tableau file for visualisation Tableau Dashboard Link: https://public.tableau.com/profile/dnyanesh.desai#!/vizhome/Visualization_1_7/Dashboard1 Tableau Dashboard Information: 1. Tax Payer Density Vs No. Of Tax Centres Map describes the density of tax payers per postcode along with the number of tax help centres in the particular postcode. 2. Individuals served by each Tax Centre Map helps to see how many number of individuals are served by each Tax centre. This helps to identify the load on each centre. 3. Data Table for Postcode Information This data table displays the history information for postcode selected by the user. Overall the visualisation allows the government to decide the location of the new tax help centre considering the growth of count of tax payers & the load on the current tax centres in any postcode.
Project HackYeah 2018! HackYeah2018! Canberra 8 15 Looking to Learn about BigData, OpenData Sets, data visualisation and interpretation. Once upon a time some technophiles thought it would be a good idea to learn about big data. ::Challenge:: Protecting our Carers: We took data from DSS and produced a heat map across Australia of young people who receive Carers payments to gain insights into their location to try and help identify how to best identify potential carers. ::Challenge:: Saving Lives through Data: Limited Public Data. Simulated Internet of things Hospital of the future and how that might be visualised. ::Challenge:: Healthy Canberra (ACT Regional) Healthy Communities (National) My Canberra (ACT Regional) Caring Canberra (ACT Regional) ::Solution:: We took data about facilities, points of interest and scenic spots in a local region (Canberra) and have used that data to visualise, analyse and provide info in the form of a mobile app connecting people to amenities, bike trails, basketball courts etc. By superimposing a range of datasets onto several maps, we also gathered a range of insights to help inform Government decisions about the positioning of public amenities and safer cycling paths. The app would also serve as a feedback channel where people can report hazards, rate the cleanliness of public facilities, and point out new locations for others of the community to get active!
project.JNav Job Nav Mount Gambier 8 5 Our idea is basically an app that shows you jobs in any area and the level of education a job needs, how easy it is to get employed, what the cap of pay is, how often are raises, what working hours there are and where the jobs are most common. Besides from that it also shows the available jobs with interview times. we chose to use these data sets because it nearly instantly clicked when we saw them to make an app for employees and employers to more easily get jobs and advertise jobs.
Project Road Federation University Casey 3 3 # Project ##The problem Vicroads manages approximately 23,000 kilometres of arterial road network across Victoria, which is worth over $20 billion. Imagine the maintenance upkeep for such an infrastructure. Current systems involve periodic inspections of roads. The current process for this involves - Manually checking - Complaints to council/vicroads - Time based not info based - Doesn’t take into account local conditions, geography, weather We set out to assist in improving this process. ##The solution Project Road uses VicRoads traffic volume data to show possible hotspots of road damage. Using VicRoads Crash data we can also see a link between heavy use roads as well as damaged roads and crash incidents. The BOM Australian Landscape Water Balance data would allow Project Road to make predictions on road degradation due to landmass changes. ##Long term Project Road would benefit from the development of smart integrated devices that would provide direct information about roads and what condition they are in to then further help road maintenance crew find roads that are failing due to unforeseen events like weather affecting the underlying water ground moisture and crashes that could affect the road and its structure. # Data Story ##Traffic Data The Data that we used for Project Road was the Traffic Volume from Vic roads. This data was used to show the amount of volume on most roads in Victoria. This Data helped us look at major roads that might need to be looked at due to the volume amount. ##Crash Data We looked at Traffic Crash Data for 2017 from VicRoads to then determine where certain points of interest might be for road maintenance due to collisions leading to damage of the road during the crash. ##Weather Data We used the data from BOM to check possible correlation between water balance and possible road maintenance due to the soil moisture and deep drainage as this could lead to road degeneration.
Project X Tech Monkeys Albany 2 3 Recommending tourist spots based on local weather conditions and planing transportation. The goal is to increase job opportunities by attracting more tourists to regional areas. B.O.M will be used for collecting rain fall data. WA Data: Geographic Names(Popular locations around Western Australia) WA Data: Public Transport Western Australia.
Project X-chatbot Team UTS MDSI -Chatbot Sydney 6 0 Making open data more open is what keeps Eda awake at night! Eda will help you find open data sets, perform preliminary EDA and mash data sets together!It is a new way to look for and interact with datasets, it should make the task of reviewing many open data sets much easier. We are a bunch of data geeks frustrated by the interface of the open data websites to get correct datasets. So we have come up with our own chatbot to improve user experience by finding the relevant datasets.
#qldanzac BigDataBuddies Remote VIC 3 5 Create a showcase of WW1 Content (QLD focus) using modern applications to help connect current and future generations of Queenslanders connect with the legacy of WW1. Project Goal: Connecting current and future generations with the legacy of ww1 as Robyn from the State Library of Queensland Said said the art of Story telling and pictures are powerful pictures tool which can help us acknowledge understand and share the history of people lives. This instagram account aims to tell a meaningful narrative through the images, diaries and manuscripts that honour and embrace the Anzac spirit. Not only do these images celebrate the end of the war and the lives of the men and women served away and at home, it links the current generation together link never before. #tags, slideshows, narrated pictures deliver maxim impact at a time where social media attention spans are limited to a swipe.
QLD Government Service transaction Behaviour and Preference Discovery Team So Good Brisbane 4 3 We are keen to resolve the problems that are related to our daily life. We love to play around with data, getting insight into data. The interactive dashboard is published on: https://public.tableau.com/profile/gavin1686#!/vizhome/Govhack-Draft3_0/DemographicDashboard The source code are published on GitHub via: https://github.com/brunocyh/govhack2018_teamsogood
Quick Safe 4 Stooges Mount Gambier 5 6 Quick Safe is an app for local communities to assit them with dealing with bushfires by allowing them to see the fire risk for their area. They will also be able to see where the last resort building's are and have the option of a head count with the people in their area to see if everyone has made it. The app will also alert them if there is an update near them and provide information on what to do. The CFS will be able to see where people are in at risk areas when they are not in a safe location (have downloaded the app). In the data we are using the fire danger ratings on the homescreen of our app which will give the user the fire risk of their location. Bushfire last resorts we have used on the maps which shows the user the closest last resort buildings for them. Using the "Number of Properties by Street and Suburb" data it gives the users a list of the people in their area so when they go to the last resort which they have found on the map they can have a head count to see who still has to come. "Precis forecast" – each State in Australia has the weather data for the day the user is on the app and the future weather which tells them the risk on a fire in the coming days.
Ready Aim Fire Ready Aim Fire Adelaide 5 3 When there’s a bushfire coming, you and your family's survival will depend on how prepared you are, and the decisions you make. People who prepare their homes for bushfire season and practice their survival plans understand what works and are most likely to survive. Most people who die in bushfires die leaving their homes at the last moment. Prior Prevention Prevents Panic. Ready, aim, fire! Starts with the data in the CFS 5 Minute Plan which populates the app. Gamification prompts are driven by conditions and timing primarily, along with the spatial data. Emergency triggers and warnings of increased risk would be driven by EPA air quality data, Geoscience Australia Sentinel satellite IR data and BOM forecasting in addition to existing CFS notifications. Sentiment analysis of social media and news feeds could be used to provide less prominent informational messages. In an emergency, the process to determine the optimal place to evacuate will include risk data that are a composite of known fire danger (BOM dataset), weather (BOM dataset), topography (OpenStreeMaps dataset), road works (DPTI dataset). Thus, a shorter riskier route would be deprioritized versus a longer safer route.
ReComp #overachievers52 Melbourne 2 6 Web app incentivising and educating people about recycling with a competitive edge. We wanted to take the large amounts of data about recycling in Victoria and use that to encourage further recycling. The app loads data for your local council and helps you make informed decisions about what to recycle. it also uses the data to show how your local council is performing, and the environmental impact that recycling can have in real terms. To encourage recycling, the app will be gamified, allowing users in each council to play off against other councils in a race to be the best recycling council in Victoria. We've highlighted the great work that the City of Kingston have been doing in recycling.
Recyclable Griffith Innovate: Recyclable Gold Coast 2 12 # The Problem Waste disposal is a difficult problem in our cities and towns that have to balance a delicate relationship between necessity, environmental impacts, and costs. One of the major costs in the recycling programs provided by state and local governments is the cost of sorting non-recyclable waste from the recyclable rubbish. Current solutions include better automation techniques and strategies for educating the public on what is recyclable and what isn't. The final problem is the cost of illegally disposed waste, or litter, that cost local governments over $18 million in 2017. We need a way of helping people make correct decisions for recycling, more effective education strategies and a way to incentivize and encourage more responsible disposal of rubbish. # Our Solution The team behind Recyclable have all experienced having a piece of rubbish and wondering if it was recyclable or not, having some rubbish but not sure where the appropriate bins are and wanting to know what sort of impact we're making by changing the way we produce and deal with rubbish. To address these problems, we have created Recyclable, an app powered by machine learning to provide decision support on how to responsibly dispose of your rubbish. ## Machine Learning Our service is powered by Google Tensorflow for detecting images taken by the Recyclable app. If you're unsure which bin you should throw your rubbish into, our app can let you know by identifying what your rubbish is and then advising you whether it is recyclable. A user can quickly take out their phone, take a picture and get instant advice. As we understand that different councils can have different recycling strategies, our app uses your current location and matches it with the recycling data we have collected in our database. ## Education While our app is able to provide immediate decision support, by continually using the app, users will become more familiar and knowledgeable about what is and what isn't recyclable. In order to do so, we have provided tools so you can keep track of your progress in reducing your environmental impact. You can see how much rubbish you produced and how much of it was recyclable. We can even break down what type of rubbish you had so you can make more conscious decisions when buying things. Finally, we give you the opportunity to see how you're contributing to your city and state waste disposal. Think of it as a fitness app for your environment! ## Incentives We believe that people want to do the right thing if there are no hurdles in the way and that littering is part of this. Often times people litter because they can't find a bin nearby (or close enough) and they do not see past the immediate effects of their actions. We've developed Recyclable as a communication medium between the public on one side and governments and corporations on the other side. With governments and companies working to reduce the use of non-recyclable and non-biodegradable rubbish, we can offer both parties opportunities to work together and create incentives. Imagine if a supermarket rewarded environmentally conscious customers with loyalty points. It could deepen customer loyalty and enable brands to send a strong message about their stance on environmental responsibility. With our machine learning network, we also have a unique opportunity for brands. When a user takes a photo of a canned drink, not only does our AI identify the can but the brand. Imagine being able to reach out and personally thank a user for purchasing their product but also reward them for responsibly disposing of the packaging. We have built an app with a unique approach to solving a difficult problem. We now encourage our corporate friends to work with our idea and help the environment while adding value to their brand! # Our Strategy Our data collection strategy revolved around collecting information ## Local Government Recycling Programs we have compiled a list of recycling programs from major cities and cities that have been in the spotlight for their recycling programs in the past year. This data is publicly available on the website for each local government. * Melbourne * Sydney * Brisbane * Canberra * Adelaide * Perth * Darwin * Hobart * Gold Coast * Ipswich For local governments that are not listed here, we have generated a list of recyclable items that are common across those listed above. ## Queensland Using the data sets and environmental reports provided by the Queensland Government to gain insight into the scale of the problem and identify interesting data sets that we wanted users to consume in a visual way. * Tonnage of solid waste recovered * Tonnage of trackable waste recovered * Comparison between Queensland and national average for ** Material types littered ** Average trend over time * Household waste landfilled This data was critical to our design process and making decisions on how we could gamify rubbish disposal while also providing feedback on a user's environmental impact. ## Gold Coast As we're based on the Gold Coast, we were fortunate to have a mentor from the Gold Coast City Council who specialized in their data trove. Originally we wanted to get a collection of public bins but were unable to get access to the data. However, we were advised that we can use parks, barbeques, and other public facilities as general locations due to the council's policy for providing bins in those areas. ## Machine Learning Using the Tensorflow machine learning framework, we used the publicly available Inception model for object detection. Using this as a basis, we collected more images on the items listed as being recyclable by each city council which was used for more specialized training to improve the accuracy of our AI. ## Generating Data Our final goal was to generate data so that we could having some good, old-fashioned inter-city and inter-state rivalries. How does your city compare to your neighboring city? Do you recycle more? Who produces less waste per capita? By providing this data in a fun and interesting manner, we're able to give feedback on your contribution to the city, state and, most importantly, your environment.
Reloqtr Team RGB(255,0,0) Canberra 5 13 With our capital cities overflowing, it's time for a mass sea change. Use Reloqtr to set your preferences and be connected to the hottest Australian towns and suburbs in regional areas. Goodbye morning commute! Reloqtr makes use of a range of open geospatial datasets from the ACT Government and the Australian Bureau of Statistics. These datasets provide information about facilities and services available in regional Australian towns and suburbs. These datasets were used to construct our innovate AI model which takes a user's lifestyle preferences and computes the best town on suburb to suit the user's desired lifestyle.
Remember When Remember Team Perth 10 2 Creating an application which unveils the hidden story behind historical buildings, events and locations of significance. User location is tracked via GPS and as they approach a location marked on the map, it will be 'unlocked'. Once unlocked, a pop-up with information about the location will be revealed, including old photos, history and other user stories surrounding the site. Users will be encouraged to discover and unlock further areas through tracking of their statistics and milestones such as discovering entire towns or suburbs. Please note: Prototype has only been coded with locations from the town of Kalgoorlie in Western Australia at this point. When using the 'source code URL section' Please direct the map to Kalgoorlie for a demonstration of use. Primary datasets were sourced from https://trove.nla.gov.au/ and https://catalogue.data.wa.gov.au/dataset/heritage-council-wa-state-register. Trove gives an in depth database of documentation surrounding various Australian places, people and events. The register gives a list of heritage listed sites in Australia. Combined we are able to pair large amounts of historical data to GPS coordinates on a map, allowing users to easily visit these sites with in depth relevant information at hand. Not only will visitors learn the story of historical sites, as a stretch goal we are aiming to create an environment where users can add their own stories to sites, adding first hand accounts to historical records on site.
ResourceUs ResourceUs Sydney 4 12 A collaborative job management solution to enable multi Agency responses to events and Incidents. The system merges the skills and experience of human resources and overlays environmental and Infrastructure assets that will have a impact on the delivery of the service. A key feature way to provide a mechanism where the prepared datasource and maps are available to the guys in the field when they are undertaking the task that the system has scheduled them to complete. The objective or this project was to provide a mechanism that allowed Environmental and Infrastructure datasets to be included as part of the planning process when resourcing Events or responding to Incidents. So our logic was to load all available data that may be a deciding factor for running an event or responding to and incident. A start set of data was selected thinking of key infrastructure resources that would be important fro scheduling an event such as the commonwealth Games, ( Such as toilets, Parking, taxi) Then we added a series of Environmental Datasets so that we could display that information to our users if it was potentially relevant to their event of incident response. This would be particularly relevant in the case of an incident like the black Saturday bushfires. We have provided a data checking process where user can identify, tag and even add in data that has not been stored in the main data source ( IE add in a new Taxi Stand ( not shown on the map. We have build a continuious model go ensure that the best data is available to everyone.
Responder oghacks Brisbane 5 3 “Responder” is a community platform (website) that connects the members of the community to help each other in a disaster and facilitates to coordinate efforts from NGOs and government. Data is used for preparing for a disaster, acting efficiently when is happening, and learning from it to build stronger communities. Through visualization tools, information from data sets like shelter and emergency sites and meteorology can be accessed in an easy way and timely, so that community members and organisations are ready for disasters and know how to act. By using data about demographics, priority sites can be identified and tracked, which allows government and NGOs to prevent before a disaster and localize their efforts. Also, through real time communication channels community members can participate in a “network of help” to assist each other. In addition, by tracking, localizing and categorizing the needs of the communities, government and NGOs can act more efficiently when disasters happen. All the data is processed to learn from the event and build stronger resilient communities, lessons to be applied in the community itself and shared with other communities. The next steps are to interview more potential users and tailor the platform to their needs and take the project to national level for a greater impact. "Responder" has huge potential as a tool to act efficiently during disasters and increase preparation and readiness, allowing to use resources wisely but most importantly, making our communities stronger and keeping them safe. Shelter and emergency, Meteorology and Demographics. Information from data sets like shelter and emergency sites and meteorology can be accessed in an easy way and timely, through visualization tools, so that community members and organisations are ready for disasters and know how to act. By using data about demographics, priority sites can be localized, which allows government and NGOs to prevent before a disaster.
SafeACT Team Erikgen Canberra 4 10 SafeACT is a set and forget mobile application that sends public safety announcements by way of push notifications at perscribed times customised to the individual user. Utilising a number of government data sets focused on historical road and transport data, SafeACT builds queries and returns relevant results based on the user's weekly travel habits. SafeACT's works as follows. Our user Amy, downloads the application from her handset's App Store. Amy opens the app and creates her profile. She is asked a small number of questions by the app about her weekly travel habits. Amy lives in Kingston and works a 9-5 job in Belconnen. She drives there and back every Monday through to Friday. She enters these details into her profile page on SafeACT, allows the app to send her push notifications and then saves her profile. Amy can now close the app and as long as he is willing to receive notifcations from the app, he no longer needs open the app to avail of it's beneifits. SafeACT benefits and notifcations work like so; 1. On the day Amy is known by the app to travel, the SafeACT application polls Amy's travel habits an hour before her work day normally starts, and an hour before her work day normally ends. 2. The application server then queries Google Maps, working out three of the most likely routes Amy would drive to and from work. 3. The application then polls a number of government data sets such as historical reported motorist & cyclist incidents, speeding infringements and past weather data to name a few. 4. It filters the data by the relevant info sets based on the similar as characteristics of the current day such as: weather conditions for that day sunrise and sunset times day of the week hour of the day and location proximity to Amy's likely driving route. 4. If the data returns a perceived higher than normal amount of past road incidents with the same characteristics of that time and day, the server sends a push notification to Amy's phone. 5. The content of the message reads as follows: 'Hi Amy, this is Jack from SafeACT. We care for our residents in Canberra and are letting you know that in the past, a number of traffic incidents have occured on this day along your normal route home. Please drive to the conditions, try to be aware of your surroundings and most of all, get home safely.'
SafeCasey CaseyTransformers Wyndham 1 0 This project is to compare the traffic data of Casey council and compare it against another suburb of similar demography and growth within Victoria and accordingly provide insights. By this, the purpose is to prepare, prevent and progressively reduce the accidents in Casey roads.
SafeCity JellyBeanTesters Melbourne 6 3 Create web app which visualizes the locations of safety data, cctv and public lighting, receives warnings and feedback to be sent to authorities, and features a distress signal function. Ballarat Public Lighting https://data.gov.au/dataset/c99c0bc9-7354-4da5-b730-dee8f729341f Get exact locations of public lighting to then further classify if the location will most probably be well lit or not. Ballarat Right to the Night https://data.gov.au/dataset/50fc8f90-bb4d-4484-809d-e9eb7bbfb826 Analise survey results done by the people in Ballarat. Find locations where people find safe and unsafe and plot it on the map. Find keywords used by users by describing an unsafe location. Ballarat CCTV Cameras https://data.gov.au/dataset/e99f92a8-beea-4725-9897-c1854eb9cc3d Mark locations with CCTV
Safer Evacuations Tiny Happy People Hacking Canberra 6 4 In urban emergency situations it can be challenging for first responders to coordinate their information with each other, and with the local community, to identify the safest evacuation routes out of the area. <BR> ![The Tiny Happy People Hacking](http://i306.photobucket.com/albums/nn262/Aceyducey/623a72ef-5a2d-4a64-a807-c49cfd088acf.png) <BR> Maps and schematics may be out-of-date, with some marketed routes potentially blocked permanently due to local building or environmental changes, or temporarily inaccessible due to the impacts of the emergency, such as flooded roads, car accidents or fires. This can make it hard, in real-time, to ensure people in the affected area are getting to safety, particularly when pre-planned evacuation routes may be affected by blockages or congestion. <BR><BR> Our first GovHack 2018 project, Safer Evacuations, allows first responders to model evacuation situations in urban environments, testing for choke points and adapting the model to review different scenarios where some of the safe evacuation routes are blocked. Using population, map and location data, they are able to plan for different scenarios and prepare plans to address different emergency scenarios. <BR> ![Safer Evacuations map](http://i306.photobucket.com/albums/nn262/Aceyducey/Photo3.png) <BR> <BR><BR> We've also developed Safer Evacuations to be useful in real-time during emergency situations. When an actual emergency requiring an urban evacuation develops, first responders are able to use data projections of population to understand how many people are affected and need to evacuate - and can mark blocked evacuation routes on the map, allowing them to share information on which routes are safe while also identifying where the new evacuation choke points may be forming (visualised as a heat map over the location map). <BR><BR> Using this real-time modelling, first responders can better coordinate an evacuation from any urban area, sending additional personnel to choke points to help manage the evacuation flow, and inform the public about the safe routes that authorities prefer people take out of the area to reduce the potential for people to get hurt. <BR><BR> With additional time, and applying a more sophisticated AI model, it would be possible to extend this to app environments where both first responders and the public could share relevant information, or a city authority could provide instructions to each individual or family on their specific evacuation route out of an area, and flag when they were taking an alternate, more dangerous route, and help guide them back towards safety while adjusting the evacuation routes for others to minimise the occurrence of chokepoints. <BR><BR> The ability to mark unsafe areas and safe evacuation routes would also allow first responders to map specific routes they need to keep clear to bring in emergency vehicles to help the injured, keeping these clear of evacuating citizens, who would be directed to other safe routes via the Safer Evacuations service. <BR><BR> Safer Evacuations will help first responders across Australian and the world to improve their urban evacuation planning through testing different emergency scenarios. In the unfortunate event where an emergency occurs, the service will support first responders to map the safe routes out of the affected area, reallocating their forces in real-time as the situation changes to help direct the public to safe evacuation routes while managing chokepoints, allowing them to reach safety without impeding official emergency relief operations. To build this model we've used an openstreet map base, and an opensource script for modelling the movement of the people as they evacuate, supported with government datasets to define the population levels, key points people would be leaving from to evacuate, and the key locations they will evacuate to. <BR><BR> It would be possible to expand these to include electoral and council boundaries, and to incorporate other geospatial sets detailing key landmarks or other relevant structures and green spaces. <BR><BR> It would also be possible to extend Safer Evacuations to non-urban areas with the incorporation of relevant datasets, to address emergency situations such as large bushfires, earthquakes and similar situations.
Safety Net #overachievers52 Melbourne 3 5 App that educates people about being scammed, with a gamified aspect. When doing our research we found alarming stats on the number and the dollar value of scams and phishing attacks, and we've all had family who has asked us to take a look at an e-mail because they thought it was legitimate. The data shows us that education is more important than preventing scams at their source, and we used that data to form our idea of educating users through examples and interactive learning. Our resident educational scammer, Sam, would be built out using machine learning and natural language processing to create a truly personalised and realistic introduction to scamming and how easy it can be.
Save life with data Team 273 Melbourne 3 3 Intent of this project is to help Australian medical society.This works by collecting different types of medical data and generating insight of the medical situation location wise and helping them to arrive at intelligent solution. https://steemit.com/actifit/@dreamzchm/actifit-dreamzchm-20180628t135908594z Added in data set on gov hack under challenge. Prototype has been developed by mocking data
Save lives with Data Nobody Darwin 2 3 We created a bubble map across Australia to showcase the mortality rate and build a chatbot were people can access it 24/7 We created a bubble map that span across australia that indicates the number of mortalities around australia
Scammy Box of Nerds Melbourne 6 2 Scammy bot is an intelligent bot being trained to communicate with members of the public and identify all sorts of scams. Scammy is also a Chrome extension that alerts users when they visit suspicious pages that may harm users, for example, shown on the right is a scam email that links users to a web page trying to impersonate PayPal. Scammy uses data on common scam vectors and methods to construct a model that it can use to identify scams and communicate with users on what to do.
Searching to Build LifeSavers Sunshine Coast (USC) 10 10 We believe that access to real-time data will aid disaster relief services and assist in the rebuilding and management of past present and future assets. We believe that in emergencies, consistency is key. Consistency in data and communication holds the keys to successful asset management and mobile asset location services. Our product, Searching to Build will provide end users (businesses and citizens) the ability to access underground services' locations and state/local government the ability to manage and edit existing data models whilst in the field to attach photographs and comments. End users will benefit from time reductions in disaster relief as this tool will eliminate the dangers of locating/rupturing existing assets and allow small-scale works to move forward quickly. Government bodies will benefit from major cost reductions and will expect to have convenience and swift transactions with the NDRRA. Utilising multiple data sets and collaborating with programs and councils, it was decided that access to critical underground and above ground council and network assets was difficult, unreliable and timely or unavailable. Further investigation leads to the discovery of some city and regional council online mapping services.
Secure your future Big Orange Brain Melbourne 3 5 Big Orange Brain is a team of two, with software engineering backgrounds and a keen interest in open data. Our aim for this year's GovHack was to uncover insights into better utilisation of our labour market that the Department of Jobs and Small Business will hopefully find valuable. Datamining the Employment Fund, Job placements and Employment projections data resulted in two key outputs: 1) the opportunity to connect Job-seekers who were previously self-employed to those seeking establish a small business 2) developing a lo-fidelity digital prototype</a> that allows any job seeker to identify where there is demand for their current skill set, and whether this is a growing or diminshig industry. The prototype can be found via the homepage link below. If you have any feedback please feel free to add your comments on our Video link below.
SeeChange Hack aPEEL Mandurah 3 7 GovHack Admin: There are two links for evidence of work. This is stopping the below button working. Links are here https://drive.google.com/open?id=1w_IJOBAMD-c2NgTzHUNw-IvCe19MVOzA; https://github.com/seanjen/seechange.git Introducing - seeCHANGE seeCHANGE is a simple interactive tool that allows people living in urban areas to visualise the possible economic and lifestyle advantages of relocating to a regional centre. We engaged design-thinking principles to truly empathise with the potential user of this tool, to create something that is beautiful, simple and provides powerful reasons to consider a sea-change to a regional area. The tool seeks to encourage them to think outside-the-box of the city limits and find a their ideal home based on what's important to them. There is an overwhelming amount of information out there that can take hours and hours and days to research it all. We wanted a solution that was easy to use and provides the latest relevant information and is tailored to an individuals needs. This tool is a solution that would pulls the latest data from: -ABS regional statistics, which include census data such as income, mortgage and rent payments, and information about population and population density. -Mapping tools Nearmap and Google maps to measure the distance of each of our regional centres to the Perth CBD and to the nearest swimming beach. -data.wa.gov.au to gather cost of living data from the Department of Primary Industries and Regional Development -Living in regions survey The seeCHANGE tool begins by simply asking the user to input their current postcode and budget (<$500k, $500-700k, $700-$1m, $1m+). The user is then asked to rank their what is important to them through a series of 'drag and drop' and sliding scale questions between not very important and very important. This includes proximity to the beach, proximity to a CBD, cafes & restaurants, arts & cultural events, sporting clubs, health services, mobile and internet quality, green space and parks, transport, crime and the ability to walk to work. Results are shown of regional areas that best suit their lifestyle preferences, ranked accordingly. Clicking on one of these areas will: -Provide a brief bio of the town -Compare what you can purchase with your provided budget in the suburb? (ie. for $700k you can get a old 3x1 townhouse in Leederville or a beachfront 4x2 house in Mandurah) -Compare data around lifestyle preferences in current suburb vs suitable regional towns. Ie. access to nature/parks (through protected areas total %), proximity to the coast (distance to nearest swimming beach by road) etc. The aim is to surprise the user with insights they may not realise around the highlighted regional towns. This is a consumer facing tool but highlights the detailed reports and data Department Regional Development has collated on the regional towns of the future in a exciting format. With more time we would like to build out the profiles of each suburb. This would include featuring top local attractions, restaurants or beaches and events happening that month. These review-based sites provide a strong case of support for the regional area through social proof. Current house listings will be shown according to their budget requirements. An added question of 'what is your occupation?' would allow us to pull current job openings for similar positions in the recommended area. Each of these can be embedded through the API's of Google My Business, Trip Advisor, Seek and Domain respectively. This provides a seamless experience for those who wish to further explore the opportunities to relocate to a regional hub and allows users to take action immediately. It is not simply a tool for providing information, but allows action to be taken. For individual circumstances there is ability to specify criteria such as under Health – that the local hospital has a kidney dialysis unit for a child. Or that under Education – there must be a private secondary school within 50 kms. The team would seek to push the tool through media outlets. Our solution to the challenge allows people of all different ages, backgrounds and budgets to easily find information about which of WA’s regional centres will suit their lifestyle and economic situation. This individualised tool is a powerful way to attract urban dwellers to relocate to regional areas, to make sure that our vibrant regional centres can grow and thrive. We wanted a solution that was easy to use and provides the latest relevant information and can be tailored to an individuals needs so we developed an App as it was a solution that would pull data from: ABS regional statistics, which include census data such as income, mortgage and rent payments, and information about population and population density. We used mapping tools Nearmap and Google maps to measure the distance of each of our regional centres to the Perth CBD and to the nearest swimming beach. We used data.wa.gov.au to gather cost of living data from the Department of Primary Industries and Regional Development In the app, this data then compares to their current town they are living in and firstly using that town, shows the user whether it is better or worse and where other opportunities are. We have also included a wildcard town to encourage them to look at towns that have the highest rating score which they may not have thought about. One of the main factors was distance and using the Perth CBD as the core, asked the question if it matters and how far. We also came up with a number of other economic factors such as housing affordability, income earning potential, and cost of living. We came up with lifestyle factors such as access to nature and parks, arts and culture events, cafes and restaurants, opportunities to participate in the community. Of course, access to basic services such as health and education would also be important. To respond to our chosen challenge, we also needed to define what a ‘regional centre’ is. Informally, a regional centre is a larger regional town or City that is generally a support centre for smaller surrounding towns. It has a larger population, and more Government services and shops than your typical small country town. We chose to go with the regional centres that have been identified as potential centres for population growth by the State Government. These include the ‘SuperTowns’ and selected towns for the Regional Centres Development Plan. To narrow it down we chose the 10 regional centres in Southern WA - covering Peel, SouthWest, Great Southern, and Goldfields-Esperance. We wanted a solution that was easy to use and provides the latest relevant information, so we created an App that pulls data from: ABS regional statistics, which include census data such as income, mortgage and rent payments, and information about population and population density. We used mapping tools Nearmap and Google maps to measure the distance of each of our regional centres to the Perth CBD and to the nearest swimming beach. We used data.wa.gov.au to gather cost of living data from the Department of Primary Industries and Regional Development In the app, this data then compares to their current town they are living in and firstly using that town, shows the user whether it is better or worse and where other opportunities are. We have also included a wildcard town to encourage them to look at towns that have the highest rating score which they may not have thought about. This challenge is highly relevant to Ollie and Charlie, two members of our team. Ollie and Charlie both currently work in Mandurah but are based in the Perth CBD. They choose to do this for lifestyle reasons but are considering the move regionally.
See the sea L.E.S.S. is more 2 Mount Gambier 7 4 An interactive website that teaches students what and where the flora and fauna are in the ocean The data story is in the Wix website
Shaping Australian Stories TeamX Sydney 5 10 Compare, share and connect. Empowering Australians to form an understanding of how they compare to others in their demographic, connect to relevant services and share their story. In an age of social media, it seems as if everyone is kicking goals and it can sometimes feel as if you are falling behind but social media is subjective, how do we truly understand where we fit in our demographic? Introducing Izzy… Simply by asking our-chat bot “Izzy” questions about your health, wealth and lifestyle, you can gauge an understanding of how you compare and how you can better your circumstances. Izzy can refer you to the relevant Government departments that may be able to provide you support if you need it. Izzy can help also you set health goals. When your done chatting to Izzy, you can share your story that will be published anonymously on the website that will breathe life into the numbers. We started with the Australian Institute of Health and Welfare's (AIHW) 'Men & Women' dataset and chose data points that could help demonstrate our concept. We then added additional AIHW datasets (full list in the data set list), and datasets from ABS, that showed binary and demographic differences between people in different circumstances. We are using the data to tell, compare and share Australian stories
SmartArt One of Many Mount Gambier 4 8 Taking Data from many different data sets, converting to graphs then into pictures and making art. I've used the Data sets required for challenges, but any data sets could be used for this project. Incorporating and Integrating Data in an Interesting way, from numbers to pictures. Mixing and Mashing Data from many data sets that would not normally or could not really be used any any real world situation. Creating the data into new views, giving insights into art with visual pictures. Teaching people some meaning of art in a new and exciting way.
Smart parking If there's time Darwin 5 5 The project explores how solar panels can be used on council land to help home renters take advantage of PV electricity production. Additional benefits include expanding shade in the city through the construction of new parking shelters. We also show how a Smart Parking app can be integrated into the solar infrastructure to make parking in the city easier. Our project is a one-stop shop for: -Helping renters take advantage of the benefits of solar power -Improving public infrastructure while cooling things down -Improving quality of living by reducing driving times and easing traffic congestion We used data from the ABS, BOM, Alice and Darwin councils and the utilities commission to determine the solar energy potential for Alice Springs and Darwin. This data can also be combined with parking data to demonstrate possible locations for future solar panel installations.
Smart Ways to Live The Capricorn Four Rockhampton 4 5 "Smart Ways to Live" is an interactive educational app that increases community resilience using a fun and innovation method. The app highlights strategies and information utilising modern technology that connects Young People ages 10 -12 to educational content that has real-life application. This app's potential is an outreach to the Mainstream Education System by utilising smart devices to deliver content that compliments existing Disaster Management literature. Our data is unique, some would say is unorthodox but we say it's perfect! We utilised the following data: - Disaster event classification, major disasters by region, Disaster ID Disaster Identifier, Disaster Event, Name, Name of Disaster Event, Disaster Event Date, Disaster, Activation Start Date, Region/s, Departmental region names used 2011-2017. This data allowed us to create and illustrate: - Checklists for the preparedness of people in the Queensland Community, and the overall preparation for their household . - identifying key costs in terms of community recovery and individual assistance grants, to build around and support relevant literature. This was made possible through the use of an information system for easy access to recovery centres in a disaster event location that can build easy connections to knowledge. Thank you for allowing us to share our story - Happy Hacking! All of this data paints a picture on how we can effectively build and create an amazing model for a social enterprise! This data has enormous potential to better inform real life disaster planning, and can have a massive impact on Mainstream Education. This app will further improve regional economic development, overall sustainability and increased awareness and education that will build resilience and create greater connected communities throughout Australia.
SoloNav Insight Hackers Casey 9 7 SoloNav Extracting information from open Government datasets can be a frustrating and overwhelming process. Data analysists and researchers spend more than 80% of their time trying to find accessible, reliable and up-to-date resources (Quora, 2018). Issues with the current open sources data bases Connectivity – there are issues with collaboration and connectivity - as Government datasets are set up to be highly siloed in specialised systems which use proprietary data schemas. Vendors have little incentive to collaborate or integrate as they have a vested interest in creating a monopoly. Therefore it’s difficult to connect multiple API’s across multiple systems into one simple solution. Complexity – there are huge complexity issues regarding disparate data sources, formats, schemas and scalability, which lead to poor data quality and low levels of data maturity across the industry. Personalisation – current solutions do not enable multiple datasets to be compared, correlated, nor customised in a way that can be easily tailored to suit the needs of the individual user or benefit the community in a meaningful and collaborative way. Benefits of SoloNav Accessible - SoloNav provides a one-stop shop where users can access multiple open datasets and derive searchable metadata in an efficient manner. User Friendly - It enables users to find insights in a quick, easy and simple way, when navigating through multiple complex data sets Story telling – users can extract and tell powerful stories through correlations of different features and datasets, using data journalism and visualisation. Insights – users will feel more empowered to make better decisions, by identifying the latest performance trends and insights. Community – SoloNav helps to bridge the gap between academia and industry, and helps to increase collaboration, innovation, awareness and deliver better services for the overall community. Sustainable– SoloNav enables councils to provide short and long-term recommendations for local initiatives, to help reduce environmental impacts and stimulate local communities’ economies. Which data sets were used? Here are some examples of the used data Australian Bureau of Statistics Description of Use: Used to download detailed statistics from 2016 Australian Census. Data was used to compare different municipalities (Kingston, Casey & Wyndham). Individual Council statistical data sets were analysed and compared to the raw ABS data and combined to provide a demographic profile of the three municipalities. VIF 2016 LGA Kingston - Description of Use: The one page summary was analysed to find key insights of the Kingston demographics, this was then used to download additional raw data from the ABS Table Builder. Australian Institute Health and Welfare (aihw.gov.au) Description of Use: This data was analysed to determine whether there is an increased cost to government for health care due to our ageing population. This was used to reinforce the Ageing population statistic as the key statistic to focus on as a performance metric.
Solving Insolvencies DataCake Sydney 9 34 We want to help Australian to be in a better financial situation. Our goal is to avoid another GFC or any other financial crisis. This is the reason why we wanted to work on the challenge related to insolvencies. Our approach for this hackathon was to integrate large volume of data across multiple governmental agencies and analyse the main contributing factors impacting insolvencies in Australia. https://public.tableau.com/profile/william6478#!/vizhome/GOVHACK/Main?publish=yes What we did: - We integrated more than 20 different datasets from different governmental agencies - We built a dataset with 200 different variables - We used a combination of Machine Learning and Advanced Analytics to derive additional information - We focused on interpreting our models outputs in order to derive meaningful insights. We are against black-box solution - We built an interactive dashboard to explore all these informations Our solution helps to: - Explore different datasets we integrated - Compare different SA3 areas on the different accessible variables - Understand the factors that are impacting insolvencies ratio
Space Project Proposal KinderGeek Mount Gambier 1 1 This video is about nasa , spacesuit technology with my rocketship design. NASA open data sets are amazing. The data sets explain the general benefits of spacesuit technology and the implications of this.
SparkLife Giraffii Canberra 4 4 Our goal is to improve the health and lifestyle of people using our application. Using open data such as public facility locations and health surveys. SparkLife is an application that allows everyday people to improve their health and well-being through a series of recommendations for physical exercise and a suitable location for it. Users can select their area and age group and be provided with some health risks for their age demographic. It will also suggest a series of exercises that are suited for them.This application will streamline and guide the user through the process from the beginning to the end. The key to a healthy lifestyle is now just one click away. We hope to connect people through physical activities and promote healthy communities. We are passionate about using data to improve our community. In particular, we wanted to focus on improving the health and well being of people. We found datasets about public facilities and combined them with datasets about health.
Spatial Team UTS MDS Spatial Sydney 3 2 A mashup of ABS census data and the ATO occupation data We have built a map that shows you where you can live based on what occupation you have. This can help people make better education and training decisions
Storytelling in 3D HyperSphere Brisbane 1 18 My project raises awareness about Queensland's immigration history by using a large, rotating electronic globe to show people how Queensland was settled between 1848 and 1912. The globe begins at 1848 and shows the trajectories of immigrant ships arriving in Australia between 1848 and 1912. It then shows current immigration patterns by showing the trajectories of aircraft. Finally, a large wall is built around the globe that will contain photos from 1848-1912, and people will be able to compare them with modern-day photos by using a slider. The main dataset I've used is the Assisted immigration 1848 to 1912 dataset, which contains the age, ship and arrival date of immigrants who arrived in Australia during this period. By combining this data about the ships' origins, the trajectories of ships arriving in Australia can be plotted on a globe, which can help people visualise how Queensland was settled, and from which countries those immigrants came. The main reason I chose this dataset is that it contains a large number of people and was collected over a long period of time, thereby allowing the globe to run for several minutes without running out of material. The other important dataset I've used is the collection of photos from the Queensland State Archives, which will allow people to visualise what life was like for these early immigrants, and compare it to their own. This is achieved by putting the photos on a wall surrounding the globe, and allowing people to compare the photos with modern ones by moving a slider. Ideally, both photos would be of the same object, to make the comparisons easier. The main reason I chose this dataset is because it's the most comprehensive collection of historic Queensland photos available. When these two datasets are combined with historic ship data, they tell a compelling story about how Queensland was settled and what life was like for these early settlers. The story begins with the immigrants leaving their home countries, sailing from one side of the world to the other, and arriving in Queensland. Once they get to Queensland, they start a brand new life, which is very different to today's immigrants. Hence, the story ends by showing the trajectories of modern-day aircraft arriving in Australia, carrying the next generation of immigrants.
Street Safe Coders Unite Ballarat 3 3 Are the streets you're about to travel on safe? When & Where are you travelling? Hows the Weather looking? These parameters have a major influence on the Accident rate on any street
Take Me Anywhere Error 417: Expectation Failed Brisbane 5 13 This project aims to connect people seeking a career change with current job opportunities in Queensland’s Tourism industry. We’ve created a website with unique algorithms which search job descriptions based on skills and locations to match them with local council and rural business opportunities. This is a great way of finding the right people with the right skills for the right jobs in a way which supports rural Queensland communities and new or growing businesses. Primary link: https://govhack2.herokuapp.com Alternative link: https://myapp-ftwwqfgsix.now.sh/search The first dataset we investigated when we began this project was the 'Deloitte Access Economics – Australian Tourism Labour Force Report 2015 -2020'. This report informed our entire approach to this project as it made us aware of the prevalence of skills misalignment in the tourism industry. A lack of skills or lack of appropriate skills was highlighted throughout the report as a key issue for tourism industry employers. This problem influenced our idea to have a skills-based job search platform for Tourism which allows job seekers to find opportunities that best align with their skill set. Through further investigation into this report as well as those provided on the Tourism Research Australia website, we found that our engine should also account for the differing requirements and capacities of each Region of Queensland. In order to do this we used the Tourism Research Australia 'Regional Tourism Satellite Accounts' for Queensland to inform our Search engine ranking algorithm. This algorithm ranked which jobs would appear in which order for every search according to the 'number of skills matched' to the job description and the 'Regional Weighting' figure. The regional weighting figure defined the potential change in tourism employment for this region into the future (e.g. will the region have growth in it's tourism employment over the next few years or a reduction). To determine the region weighting we used the Year-on-Year change value (%) in tourism employment for each region of Queensland from the 2015-16 period. This value was used as it was available for the same time period for each region of Queensland (allowing for comparison between regions). We acknowledge that this figure, as it only pertains to the 2015-16 period, is not ideal for a predictive model. In future iterations we would request ABS data, for the Tourism industry specifically, to ascertain a more accurate predictive figure. In future iterations of the project, we would like to create a full database of job names, tags and skill requirements from public job listings using web crawlers. We can then use dynamic models and machine learning to generate relationships between these elements based on their strength of connection. This way we will have a constantly-shifting, computer-maintained database of skill and job mappings for our search that can reflect the constantly shifting job demands of the real world.
TARU TARU Hobart 2 4 Deep sea fishing is always challenging. Without experience and proper knowledge, many fishermen might toil the whole day without success. TARU can predict best fishing locations for commercial deep sea fishermen based on weather, solunar (Solar and Lunar) data, satellite images, and sea temperature. An intelligent web service will inform the locations based on SST (Sea Surface Temperature), sea current, and color of the water (Based on the Chlorophyll data). TARU is ideal for commercial fishermen to plan their voyage and find the temperature breaks and swell breaks using the latest satellite imaging technologies and meteorological data sets. Fishermen those who registered to this valuable service will get their notifications real-time. So that they can plot their course effectively. This will help to decrease the overall fuel consumption in commercial fishing endeavors. Mostly fishes like to stay in their comfortable sea temperature zones. They usually swim across the temperature breaks to find their comfy zones. These breaks, therefore, will make very good areas for small fishes as well as big game fishes. Apart from that using clear satellite images as well as Chlorophyll datasets published by IMOS, we can define the areas where Chlorophyll are. These green patches are also proved to be very attractive areas for small fishes as well as big game fishes. Not only the sea surface temperature, the direction of the wind also very important factor when fishing. According to most experienced fishermen, fishes usually bite when the wind is westerly and southerly along the warm current in the temperature breaks. It means there is a very high chance of taking bites by the fishes like tuna, marlin or mahi-mahi when the winds are coming from the west, south-west, south. But very less chance when the wind is directed from North. This software will process the SST breaks (Warm Streams), wind direction, wind speed and many other fishing factors used in offshore fishing. Real-time SST, wind direction, current data retrieved from BOM (bom.gov.au) for highest accuracy and predictions happen through data classification through decision trees and AI algorithms. Chlorophyll data set retrieved from IMOS and AODN (Australian Ocean Data Network - Open Access to Ocean Data) portal
TaxHelpCenter AI Tax Enthusiasts Canberra 3 3 **We used machine learning to calculate the predicted impact of adding a new tax center at any particular postcode.** The impact was measured in terms of the number of tax returns filed and the total, which hopefully allows the ATO to identify the best locations for new Tax Help Centers which benefit the most people. It's important to note that the model we developed is extremely flexible, and is not at all limited to predicting the effect of adding new Tax Help Centers. There are some 400+ input parameters that can be adjusted. We could, for example, use it to predict changes in taxation due to demographic shifts with respect to age, sex, occupational status, etc. . # Preparing datasets o calculate the fraction of tax returns filed, we need to know the total number of people who ought to have filed tax returns in each postcode. The ABS data included in `atoabsgovhack2018.csv` is general population information, and not specifically about the working population. We can get the working population in each postcode from GCCPOA G43. However, the data is also paramterised with respect to age and sex. 1. Marginalise G43 over age, sex, to get working population in each postcode 2. Append ATO data in `atoabsgovhack2018.csv` with the results from (1) As postal area approximates postcode, we could perform a join of many datasets seen in `munging/DataMunge.ipynb` trivially. There were only ~400 postcodes where tax help centres were built (or at least labeled). We labeled the remaining postcodes as having no tax centre, this allowed the machine to learn from both positive and negative information. We were left with ~2500 rows and ~450 columns, in the analytics that we have presented as Combined ATO and Census we have given all of this information to the machine to learn from. With the analytics labeled ATO only data there are ~40 columns. # Building Models Given the mix of continuous and discrete types in the data, and the relatively small size of the sample set (i.e. number of taxed postcodes), we have used a gradient-boosted regression tree (GBRT) method. We have employed the DART tree booster (described in Rashmi Korlakai Vinayak, Ran Gilad-Bachrach. “DART: Dropouts meet Multiple Additive Regression Trees.” JMLR.) which adapts dropout regularisation from deep learning to boosted trees, ameliorating the tendency of these models to overfit their training data. The model hyperparameters were optimised using a hybrid coarse grid-search and meta GBRT optimiser We trained models using a subset of the ATO data only, and another model which used the combined ATO/ABS data. We found that the ATO data was overly optimistic about the impact of a new Tax Help Center; whereas the model trained on the ATO/ABS data was somewhat pessimistic. We included interactive graphs of both models for comparison.
Tax Help Helper Team 304 Brisbane 2 2 We are a team of data analysts in Brisbane whose membership is comprised of Brendan Sulivan, Mathew Taylor and Luke Ginn. Our project is called Tax Help Helper and we believe this is the solution to ‘The Friendly ATO’ and ‘Tax Return Help Centers’ challenges. Problem: Without previous experience or support, understanding how the tax system works can be a struggle for new users. The Tax Help Center program provided by the Australian Tax Office (ATO) acts as the vital assistance to those who require this support. However, the challenge facing the ATO is on where and who needs this help the most. This information is key to the most effective deployment of ATO resources to support the maximum amount of people possible. Vision: Using a ‘Machine Learning’ approach, our vision is to provide the ATO the key information they need to utilize their resources to the best engagement of their clients. You can access our solution: https://public.tableau.com/profile/luke.ginn4421#!/vizhome/GovHack_2018_Tax_Help_Centre_Search_Me/SearchMe Our Video Solution: https://www.youtube.com/watch?v=f6GFw5NCS5w The information we used for this project was provided by the ATO, as well as additional information from the Australian Bureau of Statistics. Geolocation data was necessary for our project's visualization and user interface. We joined datasets together via a left outer join with all unique postcodes and used a union to combine the years together. This was done using a conjunction of R and SQL. The machine learning algorithm learned off 2006 and 2011 data. We then predict the results on the 2016 data. The model of choice was xgboost with Bayesian optimization. The objective function of the model was to minimize the RMSE (root mean squared error). The choice of the algorithm was due to it’s robust nature in preventing overfitting and accuracy, but also because it is able to handle missing data which may be a problem commonly faced by the ATO or ABS. Through the hypothesis process we looked into removing data columns for a process of feature selection. Trained on only 2011 data or the combination of 2006 and 2011. We looked into aggregating postal codes by regions in Australia for the model to learn from. After all these iterations the training of 2006 and 2011 data without an aggregation of postal codes was decided for both model accuracy and usability for the ATO. We were satisfied with the results when the accuracy was around 90% and recognized the remaining error may actually a result of a misuse of the tax help center resources and may be approaching the theoretical limit to this data science problem. To make the product useable, we published it online to a Tableau server so that it can be used by the general public or by taxation officers. This link could be sent to all tax help center volunteers across Australia or to help identify which postal codes may require tax help centers in the following years.
Tax (Help) Optimisation The Hellish kangaroos Brisbane 2 2 # Project overview The Australian Taxation Office has opened around to 500 help centers across Australia, where accredited community volunteers can provide assistance for individuals. These centers, of great help to the community, are often hard to find, even requiring a phone call to locate them. For these reasons, opening a new Tax Help center is a strategic decision, that can be supported by various AI or machine learning approaches. # Approach - Get the tax and postcode location data. - Preprocessing tasks and precomputations, such as a distance matrix for fast access to the distance between two suburbs. - Predictions for 2021. - Computation of utility scores for suburbs, indicating how valuable opening a tax office in a specific area would be. - Interactive front-end display of our results. # The factors and usage of the datasets Among the various factors that have to be taken into account when opening a new help center, for clarity and simplicity, we mainly focused on the following ones: - The population: When opening a help center, we want to be able to reach as many people as possible. - The income: Some people are more likely to be expecting a tax return, and may require assistance. Therefore it would make sense to favor the low-income areas. Based on the processing of the data available to us and our predictions, our web application allows us to visualise in an interactive way the past and upcoming situation across Australia and support decision when opening new Tax Help centers. # Future potential The dataset is much richer than what we focused on, and with enough time and computational power, there is a potential for relevant analysis of previous help center openings, as well as accurate predictions for the future. The Medicare levy surcharge, population by age, wages, gifts or donations, or HELP assessment are just some of the variables that can help to be more accurate.
TAX Mate Tartans-AU Adelaide 4 4 #Summary: TAX Mate is a solution for both tax residents and the government. For tax residents, the app provides an easy access to the nearest ATO help centres. It optimises the ATO’s resources allocation process and placement of help centres. We design the solution as a result of available open data and Machine Learning algorithms implementation. TAX Mate Mobile App will facilitate the tax residents’ geolocation and direct them to the nearest ATO help centre. Moreover, they will be able to make an appointment for future visits. The tax residents can also include additional requirements such as preferred language or the purpose of the visit. ATO Help Centre Management Suite allows ATO personnel to determine the best locations for the next ATO help centres. From the volunteer point of view, the app can optimise volunteer allocation internal processes and the selection of the places that provide the best option to meet tax residents needs. Additionally, machine learning algorithms provide the prediction of the number of offices that will be required by each postcode; therefore, a dashboard module is part of the solution to support the decision-making process. Finally, TAX Mate is a scalable solution, it collects new data that may be processed in the future to get new decision factors that increase the accuracy of the machine learning algorithms. #Benefits: The solution provides benefits not only for ATO office but also for Tax residents. - **ATO Office**. Optimise the use of resources and financial costs that imply the implementation of Help Centers. It helps to identify customers pressing needs and allow ATO to provide specific help required. - **Tax Residents**. Friendly and faster way to get help from ATO # Further recommendations: 1. TAX Mate could be integrated with Alex ChatBot to gather its information and join it into the machine learning process. 2. ATO mobile app could be used as a medium for TAX Mate marketing and vice versa, using friendly banners. 3. The production environment should consider the implementation of security controls to guarantee the confidentiality, integrity, and availability of ATO’s sensitive information, as well as the privacy of tax residents personal information. 4. In terms of marketing, knowing in anticipation the number and the places that will be used as Help Centre, ATO could implement marketing strategies to promote the use of the service, which is reinforced by customers requests. 5. TAX Mate is a system that will start to gather considerable data from the tax residents; in the near future, ATO could implement artificial intelligence to provide automated answers to the most common answers through ATO mobile app, Alex ChatBot, and TAX Mate. As a result, the need for future volunteers will be decreased. 6. The information gathered is not only useful to answer common questions but also may be used by the ATO internal departments to automate processes, update people-profile-risk maps, and track the flow of the processes. This information can be integrated with existing ATO artificial intelligence, providing a deeper insight into taxpayer behavior patterns. [![IMAGE ALT TEXT HERE](http://img.youtube.com/vi/YOUTUBE_VIDEO_ID_HERE/0.jpg)](https://youtu.be/sAPWU8lLeuk)
Team Go Get It PreventLitterforBetterFuture Brisbane Youth 1 2 Using technology to help prevent litter and make less fast food packaging going to landfill. Software is a prototype that currently works on any android phone OS version > 4.4. As a proof of concept. The data is sourced from the hackerspace data section. The barcode info is from google.
The Australia Game Work In Progress Ballarat 5 3 Learn about the demographics and stats that make up regions across Australia through a web-based trivia game! the Australia Game makes exploring the diversity of Australian communities fun through a Who Wants to be a Millionaire?-style interface. Using Google Maps, players can see the communities in question and get hints about which one is the correct answer. We've sourced data from AIHW, data.vic.gov.au and the ABS to demonstrate the diverse human geography that makes up our country. We also used Google Maps to generate a cross-referenced GIS database so that we can zoom in on the area that is the subject of each statistic when the questions are asked. The technologies used include Google Go and Javascript.
The Darwin Heatsync Project Heat Syncs Darwin 5 6 The Darwin Heatsync Project is all about harnessing the power of citizen science to drive solutions for a cooler, healthier, more connected and more economically viable Darwin. Darwin is known for being a few things – and “hot and sticky” feature high on everyone’s lists. But we’re also known for our gorgeous sunsets, incredible nature and having the best weather in the country whenever our southern friends are freezing over, or even having their January heat wave. So where are the real hotspots and coolspots of Darwin? Now famous aerial photos of pre and post cyclone Marcus, tell a story of vastly reduced greenery in the city of Darwin. Heat maps have not been created for the post-Marcus area, and we also lack more precise heat data from our key recreational and transport spots. The Darwin Heatsync Project is taking existing open data sets such as car parks, bike paths, tree cover and the greater Darwin map, and overlaying it with new, point to point real-time temperature and humidity data. The new data is citizen driven. Students and other enthusiasts are coached to build our networked and gps enabled climate sensing modules, using the Internet of Things. These modules will be hosted in multiple locations in Darwin CBD and beyond. Our website heatsyncingdarwin.net allows residents and visitors to find out where the best (coolest) picnic spots are, the shadiest spots for exercise and where more trees are needed. This means more people will participate in outdoor recreation as they can easily locate the coolest spots nearest to them. They will also be motivated to participate in greening the city initiatives as they can see from our map the difference it will make in cooling the city. The Darwin city authority will benefit by gaining Citizen generated feedback on the best spots for future constructions of green spaces, shade infrastructure, transport routes and recreational zones. The climate sensors can be incorporated into Council’s Switching on Darwin programme. CoD intends to conduct microclimate monitoring, including temperature and humidity data at city traffic intersections. The Darwin Heat Sync Project proposes using our modules at each intersection, at various buildings including offices, schools, shops, community buildings and apartments, and at regular smart street-lighting pole intervals throughout Darwin CBD. The modules will be delivered through a citizen education and engagement programme, and the public will be able to visualise real-time climate monitoring. The Darwin Heatsync project will therefore help CoD to actively engage with residents in cooling off their community. As future functionality, the website or app will permit users to input data on green spaces that they create, and apply for a financial gardening incentive. This can be used particularly to encourage small gardens in apartments in Darwin CBD. A cooler Darwin, and one that has known and available cool spots, has many positive implications for residents’ health, tourism, business and community engagement.
The Four Musketeers The Four Musketeers Sydney 7 2 Unleash the power of machine learning to predict the causal factors of noncompliance. The team delivered learning Algorithm model to predict the risk of noncompliance on case by case basis. Our team built a complete machine learning model that harness large volume of government datasets from various organisations including: Australian Taxation Office, Australian Bureau of Statistics and Australian Government Financial Security Authority-non-compliance in personal insolvency data.
The Hecs prize - Bounty: Industry meets Academia Jurisdiction: Australia Hecs prize Toowoomba 1 5 We entice the formation of game-changing startups and visionary collaboration through incentivized competitions that encourage the creation of unique IP and sustainable outcomes A yearly competition that brings together teams of industry (business) and researches (Higher Education) to deliver new Intellectual Property and Commercial ready products with prizes and potential investment. #**The Challenge I am addressing today is** How can we overcome the cultural differences between business and researchers to encourage innovation and collaboration?</p> #**Why does it matter to find a solution?** There is a whole lot of funding going into research ($10 billion a year in fact) but a lack of new intellectual property is being commercialized. Without commercialiation, Australia is falling behind the rest of the world and new jobs are not being created. It is essential that we promote effortless collaboration between industry and research so that Australia can keep up with the rest of the world and create new jobs into the future.</p> #**The Vision is** To promote and provide a collaborative community between Research and Business which will result in more relevant research and development, to ultimately produce new and novel IP that gets commercialized.</p> #**My approach to solving this problem** To research and find out why there is such a lack of collaboration between Research and Business, what current solutions if any are out there and from this data create a viable solution? Through data.gov.au I found the National Survey of Research Commercialisation 2000-2015, I found the Australian National Data Service (ANDS) which encourages collaboration between researchers which then lead me to Research Data Australia, which is datasets from research that has been performed. The data that I did find was hard to interpret and hard to navigate around. In my research I could not find a database of current research that is being undertaken or current problems that need to be solved within industry. The research showed me that there is a huge gap between research and business due to the lack of transparency from research and the lack of data from industry which I believes creates a culture of distrust and does not promote collaboration.</p> #**Solution and MVP** My solution involves making both research and business much more transparent and collaborative through the sharing of ideas and current research being performed in a year long event. We have a history of not sharing due to fear of idea’s and IP being stolen, but we know that commercialisation only happens with great execution not great IP. So by bringing both researchers and business together we can create great IP and great execution resulting in commercialisation of new IP and creating new jobs for Australia’s future.</p> #**The concept** An incentivised year long competition where researchers add their current projects they are working on and Businesses add their current problems. When these have been submitted, the businesses and researchers will join together in teams and over the course of the year work on research and development to bring a viable product to market utilising the R & D tax incentive and other grants that are available. At the end of the year, teams will then come together to pitch their solutions in front of judges and investors and the winning team will have their Hecs paid off for the researchers and the businesses will have a new and innovative product that will potentially gain funding from investors. </p> #**The impact of running this competition** Will bring researchers and businesses together, creating innovative products and solutions to market which will help grow our economy and create new jobs for the future.</span></p> #**What are the next steps and how will we move forward?** I have already started building out the web platform and can have this completed within a week. I will then be getting other team members involved from the startup community I am involved in from River City Labs in Brisbane to Canvas Coworking in Toowoomba, the Sunshine Coast Gold coast and the huge startup community I am involved in. We will be communicating with Universities and industry to get the projects submitted and can start rolling out the competition from the beginning of 2019. This Competition can be run each year with the support of government and sponsors, with potential partners including CSIRO, Universities, Innovative Industries, Venture Capital and Government.</p> Through data.gov.au I found the National Survey of Research Commercialisation 2000-2015, I found the Australian National Data Service (ANDS) which encourages collaboration between researchers which then lead me to Research Data Australia, which is datasets from research that has been performed. The data that I did find was hard to interpret and hard to navigate around. In my research I could not find a database of current research that is being undertaken or current problems that need to be solved within industry. The research showed me that there is a huge gap between research and business due to the lack of transparency from research and the lack of data from industry which I believes creates a culture of distrust and does not promote collaboration.
The mystery of history L.E.S.S. is more 1 Mount Gambier 7 8 An app that scan Qr-codes and gives you the history and current information on the scanned sight Data story is noted in the Wix website
The Next Busker Shooting Unicorns Melbourne 6 5 Buskers have been part of cityscapes for centuries with many governments embracing them as a cultural asset. They play a role in making our city more vibrant and lively and are strongly supported by the community. However, busking isn't always as easy when there are: 1. Strict regulations (i.e. 2 hour time slots) 2. People carrying less and less cash 3. A lack of resources and technology available For GovHack 2018, the Shooting Unicorns team created 'The Next Busker', a platform using open data for buskers to identify the best time and location to perform. The platform analyses data using pedestrian volume to determine hotspots for getting the best audience reach. The platform also allows buskers to be discovered by Melbournians and tourists, schedule their performance time to notify followers and the ability to get paid online. For the community, this is a platform that brings people together to discover, subscribe and support their favourite buskers. we're also experimenting with other datasets to implement even cooler features for the busking community, such as re-purposing under utilised parking bays for even more space to perform at and in the future weather data to improve forecasting. To help buskers identify the best time and location to perform, we aggregated pedestrian traffic to determine the average count for each sensor by week day and hour. To use this data in a meaningful way while factoring in good user experience, we built a map allowing buskers to select a time and date that fits their availability. Using the City Of Melbourne's Open Data SOCRATA API, we then filtered sensor locations based on the radius of the selected landmark of interest and displayed hotspot areas for buskers to choose. We also wanted to experiment with the idea of re-purposing under utilised parking bays for busking (an 'alpha' feature since it hasn't been approved by the council yet). To achieve this, the platform uses on-street parking bay sensors in conjunction with on street parking sensor data 2017 and on street parking bays data to calculate the aggregated daily usage of parking bays across the City of Melbourne. This allows buskers to also see on-peak and off-peak parking bays on the platform based on their selected time and location.
The Papa Project - Helping Oldies be Goldies TeamYFam Wyndham 10 10 How can we help councils work through opportunities brought about by the growing population in Australia? In 2016-17 $17.4billion was spent by governments on aged care however people and their family in this senior age range often are unaware of all the services and programs available to them. Our app is designed to use open government data, local council data like Wyndham's Occasional Care data set and location information to collate all the available services and program for seniors into one easy to navigate, user friendly app. This will not only help the seniors and their families find the relevant information, but the data from the app will also help inform local councils of the programs and infrastructure needs of their local communities in real time.
The Spirit Lives Living Spirit Brisbane 5 2 Marking 100 years since our involvement in the First World War, the Anzac Centenary is a time to honour the service and sacrifice of our original ANZAC. By using machine learning for colourising and 3D modelling portraits, we bring life to the past. "The Spirit Lives". Our application allows users to choose a portrait from the State Library of Queensland's datasets and automatically colourises it and displays a 3D model. The web application is used like any other website and is very intuitive for users of all ages. The back-end of the application is where all the magic happens. We have trained a machine learning model to independently colourise images without any human assistance and the 3D model of the soldier is created from an open-source repository. Our vision for this project is to bring life back to the past so that we can reconnect Australians of today with our history and commemorate those who fought for the lives we live today. How can we achieve this? We knew that we had tens of thousands of digitised images from the State Library of Queensland and we know that people of today are exposed to new technologies such as colour photography and 3D imagery. So we put these two things together.
The Wild Australia CloudBench Parramatta/ Liverpool 2 1 This project is to find local Australian animals in the wild so that people can see them in their natural habitat and appreciate them. This project usesNSW BioNet Species Sightings Data Collection to find animals in wild.
This Place This Place Sydney 6 7 Many residents of Australia hear a "Welcome to Country" or "Acknowledgement of Country" at events, but do not understand its deep significance, or the importance of country to Indigenous Australians. Many people are unaware of just how many diverse Indigenous nations and peoples exist in Australia. We have designed a site combining Australian Open data such as native title and significant Indigenous locations with a new idea - community curated Acknowledgement of Country in languages other than English. We intend to extensively SEO the site to attract curious people searching for terms such as "acknoledgement of country", "aboriginal land" and LOTE terms. This will allow all Australians, no matter how recently arrived, to acknowledge the custodians of the land and understand and explore their connection to Country. We utilise a range of seed and data.gov.au geographic data along with OpenData from other sources such as https://native-land.ca/ and wikidata along with a newly generated community language dataset for acknowledgement of country. We provide feedback mechanisms on Australian data sources to allow indigenous citizens input into how and what is presented.
To Employ or Not To Employ Potato = Not Potato Casey 2 2 Using MyVic and data.gov.au data to find how governments can best make efficient decisions to increase local employment per suburb (ie. transport, infrastructure, investment, industries). We used the MyVic mapping API (https://www.data.vic.gov.au/data/dataset/my-victoria-mapping-api-govhack-2018), with suburb specific datasets for various impactors, to find the impact of multiple features (eg infrastructure, cultural diversity, income) on employment per suburb (also a data set in the MyVic mapping API). The Public Internet Locations dataset (https://data.gov.au/dataset/public-internet-locations-vic) was also used as a feature in the model (to determine its impact on employment). This data was ultimately used to suggest efficient improvements in features in order to maximise employment
Top Trunk Team Hackers Ballarat 2 4 Engaging Councils to increase openness and innovation through a card game! Based on the popular "Top Trump" game, we play council versus council to see who is the most innovative, most open and most livable! We summarise datasets from the ABS, data.gov.au metadata, world livability and innovation centres. Data tells a story, even when it' s just top level summaries. By showcasing the comparative strengths and weaknesses of different councils, we hope to encourage them to improve.
Trailen ElectronicallyE Adelaide 5 5 Trailen is an app, connecting those who know history with those who want to know about the history. From city to country, Trailen provides networking opportunities for both locals and tourists, allowing them to be educated orally about where they are face to face. Adelaide, South Australia and Australia have a rich and vivid history which is right below our feet, providing an opportunity for people to get outside, get active and learn. Why sit behind a screen learning about history when you can witness and experience it for yourself? Users of the app are able to connect with others in addition to sharing recent discoveries made personally or via the government datasets. This provides an extension to the joint exploration and educational aspect, with such data being able to be fed back to historical datasets of government and council for increased detail and information. Educational facilities including schools can also use the application for study and excursions. Teachers and students can discover locations in close proximity to their school for practical and physical learning opportunities. Trailen uses two major dataset types as the backbone for its functionality, these being historical data and school zones. The historical data is a basis for the information present in the application. This data is used for: • Brief explanations – A summary of the locations and important information • Photos – Visual examples of the locations throughout time • Locations – Coordinates and addresses, allowing visiting opportunities This data is used in conjunction with that which is user submitted, filling in gaps present in government datasets due to the obscurity or lack of relevancy to government departments. By combining school zoning data, with historical locations, teachers and students are able know of locations which are in close proximity to the school. This allows learning opportunities outside of the classroom environment in the local community, engaging classrooms with historians and the past. It also assists to teach them about the very place they, work, live and play.
Trash 4 Cash McDumplin' Gold Coast 4 4 A gamified way to clean up rubbish (litter). This app is part of an initiative to get people to pick up rubbish and clean up. Rubbish data.
Trash Talk RoboRoyals Sunshine Coast (USC) 7 16 Trash Talk is an attractive, innovative and interactive smart rubbish disposal unit, designed to address the needed culture change that will lead us into an advanced, pristine and sustainable future. Trash Talk displays a fitted digital LCD that educates and prompts communities to use and sort waste correctly through visual aids and recognitions. It has indicators to inform users and councils of unit capacity and make suggestions to other units when capacity is reaching its limit. This ... feature allows community members on site to have live, up to date information regarding unit capacity and suggestions of nearby units to avoid overflow. Council can use this data to data inform them of all units usage allowing for optimum management of resources and funds to execute state of the art maintenance of our natural community and environment. To safeguard the bins from wildlife and help to securely store the rubbish, Trash Talk is equipped with functional swing flaps over each waste compartment. These waste compartments are only uncovered once the proximity sensor imbedded in the chassis of the bin is activated. Upon activation, Trash Talk, politely greets users, helpfully prompting them to consider recycling eligible items. Further community collaboration will see partnerships with business' to pursue our vision of Trash Talk-compatible QR codes on fast food packaging. These QR codes will allow for the disposal packaging to be tracked and synced for community rewards through a free user friendly phone app. This deep integration allows a further interactive opportunity that will see members of the community collecting credits and rewards by simply disposing of their packaging in correct bins to receive real-world rewards linked via partnership with local businesses. Trash Talk is more than an attractive, innovative, interactive and smart rubbish disposal unit, it is a leading part in creating a world wide change that educates all to help care and preserve our beautiful natural wonders. Using our data, we discovered that areas with a denser population required more bins, such as Bullcock Street, Brisbane Road, Maroochydore First Avenue, and the Mooloolaba esplanade (Public Place Bins, Sunshine Coast Council). Data Tables: Chapter 7: Cost and Funding (AIHW) major diagnostic categories supported our theory that cleanliness and public bins reduced the risk of disease within communities. The data from ‘What services were Provided’ correlates to the diseases and procedures given in each territory or state. This continued to support our thesis that more bins, means a cleaner, healthier community. Litter Counts provided information about traffic of bins. We can assume which bins in which areas are actually beneficial to the community and which are not. This allows us to create the placements of the new bins in more suitable locations, and unnecessary bins can be removed.
Trendhound DIISplay Canberra 10 8 Trendhound lets users search a keyword of interest across Twitter, Google News and public datasets. The dashboard displays relevant tweets across the country and relevant news articles. It highlights facts at the states and territory level from relevant datasets. It allows users to quickly see trends, and access data for more detailed analysis (if desired). Trendhound will benefit a variety of users, including policy makers, government service providers and ordinary citizens. Policy makers could use Trendhound to better understand community sentiment, and easily access related data to make better decisions for the community. Government service providers could use results to analyse short and long term trends, or use community feedback on Twitter to predict sources of community stress or public health issues. This can influence decision-making in real-time, for example to make staffing allocation decisions at hospitals. This will allow service providers to efficiently allocate scarce healthcare resources. Citizens can use Trendhound to see the healthcare trends and issues in their communities and how they compare to the rest of the country. In this proof of concept phase, data is at the state and territory level, focusing on healthcare issues. This could be expanded to more issues, data sets, and geographical levels. Example use cases: User Story 1 Rachel is the senior administrator of a major hospital in Canberra, responsible for, among other things, staffing allocations. A quick search of the terms “cold” and “flu” on Trendhound can tell Rachel if there is a spike of cold and flu cases in the areas surrounding the hospital. This can help Rachel to plan for staffing and other resource allocations in the hospital to ensure that resources are efficiently allocated and service delivery is not impacted by sudden changes in demand. Trendhound could be expanded to search for emergencies and other infectious disease outbreaks with similar benefits. Rachel could also search Trendhound for cancer data and trends, making it useful for longer term planning and decisions. User Story 2 Monica is a senior advisor on health policy with the ACT Government. On Trendhound, Monica can search for a number of health related keywords and gain access to a range of trends and information from sources such as Twitter, Google News and public datasets, all in the one convenient place. Monica can use the result to better understand trends and sentiments in different communities across Canberra, and easily access related data, for example community feedback through Twitter to predict sources of community stress or public health issues. Monica can use the information to make better, more targeted and efficient policy decisions that will positively affect Canberra’s communities and citizens. Check out the project on the homepage URL to explore Trendhound and see user cases. You can check out more user cases here: https://drive.google.com/open?id=1mlh_-uk4FavEQQb6iXEzrLor8s5i98L1-tpjWrVN5Vw Key Risks Trendhound can search and return results for tweets from private individuals, so there is potential for text that includes explicit material, incorrect information or other unwanted results. Information from Twitter and Google news could be wrong and lead to poor decisions being made. Searches may not return the results that are useful to users or not provide enough information to make a sufficiently informed decision. Users may misinterpret the data presented, leading to poor decisions and outcomes. Measuring the impact of Trendhound is challenging, as it is not known how many searches lead to high-value or high-impact decisions. We used data from the AWHI, ABS, ACTgovdata and data.gov.au with Twitter and Google News Services to create a dynamic interface showing key information and datasets on an area of interest for the user. Input search term(s) (hayfever, cancer, obesity, drugs, smoking and alcohol) to start searching. Trendhound: Simultaneously searches Twitter, google news and relevant datasets. Returns relevant results from the above sources for the search term(s). Gives breakdown of percentages for search terms. Links search terms to relevant datasets. Our data tells the story of the regions and people of Australia. It tells people about the issues that impact them and their neighbours, and offers the location of local services to become more engaged. It helps people find the most relevant tweets, news and datasets, so they can understand the context of their query. Our data tells a story about how communities live their lives and how they can use public facilities to make them better. It is about learning about where you are or where you'd rather be!
Umbrella SciSearch Umbrella Brisbane 1 3 Umbrella SciSearch is a search engine for location-based environmental data. Search for a location in Queensland, and SciSearch will return an aggregation of multiple types of data taken from that location. By building this search engine, we wanted to give people a fuller picture of what the environment looks like in various parts of Queensland. It's easy for researchers to focus on the type of data they specialise in above all else - but it may be useful for them to see how other data fits together as well.
Uno Uno Future Adelaide 7 5 Team ‘Uno Future’ have created ‘Uno’. Uno is a simple way for businesses and people to come to together making what they are already doing much easier! Uno uses Near Field Communication (NFC) which is already in more than 60% of mobile phones in Australia to collect data from events and transactions it organised. Uno’s data is displayed in a dashboard that provides insights for Government, Local Councils and Business Owners so they can make better, more informed decisions. Project Evidence on Google Drive: https://drive.google.com/drive/folders/1HARRoqJYlMWD0gSIfbR5iGnzvWAIFuLi?usp=sharing Project video: http://uno.digitalcoffee.com.au/video/uno.mp4 Uno currently uses four Local Council datasets on ‘Outdoor Dining’, ‘UPark Available Spaces’, ‘Bike Racks’ and ‘Events’ and also national ABN Extract data. These datasets have been chosen as the best fit for our Hack. Team Uno Future envisage using new and wider datasets to be able to list more businesses and relate more services to make a wider reaching and more valuable system.
Urban Hob·art Project Art Hobart 4 2 The city of Hobart is fortunate enough to host an impressive collection of urban artwork, which is noticed and admired by locals and visitors alike on a daily basis. However, these diverse pieces of artwork are often difficult to locate, and are lacking additional context about the artists, and the vision behind the artworks' creation. Our project aims to bridge the gap between Hobartian and artwork, by creating a comprehensive directory of the urban artwork that exists around Hobart. Visitors to the site will be able to locate various pieces of artwork in their current location, and see additional information about each piece of artwork, including who the artists are, what materials the artwork was created from, when the it was created, and, most importantly, where it is located. Of special interest are descriptions of the artwork provided by the artists themselves, who share intriguing insights into their ideas behind the artwork's conception, and its original purpose. On the application related artworks are grouped together, so visitors can discover related pieces of artwork such as artwork by the same artist, part of a single collection, and created with similar materials. One of the most important features is a fully interactive map that is constructed around the visitor's current location, and allows them to discover artwork in a close vicinity. With this, a visitor to Hobart, or someone who lives here, will be fully equipped to discover and explore the true wealth of urban artwork that Hobart has to offer, supporting and appreciating the work of our local artists. Our project is built upon the Urban Art datasets provided by the City of Hobart council. The datasets already provided the majority of what we required, but required a fair amount of processing to transform it into a consistent and useful format. We combined multiple datasets containing urban artwork to create a more complete picture of the artwork available around Hobart.
Vic Navi The Interesting Company Melbourne 5 6 # Objectives - We want to better inform citizens about the most suitable way of going out. - With the power of chatbot we can provide suggestions in natural language. - We can provide suggestions for disable people as well. # Functions - A web application provides navigation and suggestions. - A chatbot deployed on home intelligence which can provide suggestions. # Air, Weather and Tree status - The most significant features influencing out calculation of different methods when citizen wants to walk # Toilets location - For convenience of citizens with special necessary # Road congestion status - For users selected the fastest route, this feature becomes important
Virtual Emergency Management Null VRiables Canberra 10 7 <p>Thick black smoke chokes the city, as fire moves in from the West. Emergency vehicles race to the fire front, as residents, schools and businesses prepare to evacuate. As embers begin to fall on the outer suburbs, everyone's next decisions are crucial.</p> <p>Situational awareness is paramount in dealing with any emergency situation. Virtual Emergency Management creates a virtual environment that allows an emergency commander to be fully immersed in the situation, through VR, knowing the position of all their resources. The direction of the wind, and position of emergency vehicles, evacuation centres, potentially threatened lives and infrastructure are all mapped out in three dimensions. They are aware of it all.</p> <p>In the city, evacuations are coordinated flawlessly to available schools. The emergency vehicles are directed in the optimal plan to stop the fire, keeping a constant supply of water. Although some houses could not be saved at the city's periphery, no lives are lost.</p> <p>Our project places the user in a realistic environment utilising weather conditions, time of day, wind and terrain data. Using various relevant data sets within the VR experience allows for more effective information sharing and collaboration between agencies. It can also drive a more informed decision making process during domestic emergencies or national security events.</p> <p> To demonstrate this, we created a six square kilometre area in the centre of Canberra. We then fed several large data-sets from the ACT Government and the Bureau of Meteorology into the environment to create a 3D Virtual Reality Emergency management experience. Some of the data used is obviously relevant for use within an emergency, while other data sets are seemingly unrelated until viewed in this format.</p> <p> In the initial scene, emergency vehicles, displayed in Yellow, travel through the environment following the same path they took in 2016. Emergency call outs for 2016 are displayed in Red to compliment the vehicle data. Major water catchments are displayed in Blue, Schools across Canberra in Pink and sports ovals in Green. We have also used an international data-set to display airport locations to assist in managing major emergency incidents.</p>
Vision Vision Melbourne 5 4 Our idea is to organise various demographics of each suburbs, such as crime rate, nbn availability, ease of transit, that can influence people to buy (or rent) properties. The aim is to display the markers on the map which makes it easier for the user to compare various suburbs and plan their investment. Also, the government can utilise this map to do urban plannings. We will be using the open data sets provided by the government including the ones for crime rate, census, schools, jobs etc. to display markers on the map
Walk Launceston Wumble Bumbles Launceston 4 2
Walk Melbourne AR TinyIdeas💡 Remote VIC 3 3 An audio guided, multilingual, augmented reality mobile app designed for both locals and tourists to see the past history of Melbourne. Combining audio and visual, past and present data to tell a story about Melbourne's history.
Watch Out What's About? Data @ Heart Sydney 4 5 * Our project aims to be a service to Australians living their lives, telling their stories through social posts to help people to be more aware of the issues facing themselves. It aims at improving the safety and peace of mind of people in and about our great, vibrant urban, regional and open spaces. * Joining BOCSAR crime data (22 years data across NSW postcodes) with layers of geolocated, time-filtered social posts, (Twitter, Instagram and Facebook) that have been publicly posted and pinned, we process these for NLP semantic and entity understanding, in order to predict and offer insight to users of our app. The information of trend predictions of crime in locations around where they are, helps better inform them of the risks that might be experienced. This is particularly important given the #MeToo movement and tragic circumstances experienced by the likes of Jill Meagher and Eurydice Dixon, as well the alcohol related “king-hit” punch crimes that ended in the tragic death of Daniel Christie. * With our passion for data at the heart of decision making, we hope to make Australian society a better place to live, love and enjoy. * This too, would help utilise police resources patrolling areas of predicted high crime areas based on our modelling calculations in a simple to use easy to access app on a smartphone. Our layers of geolocation mapping also blends and calculates the location of pubs and restaurants to weight the variables of incidence of crime, due to such factors of alcohol consumption. The data from AIHW has added the ability to incorporate trends and predictions from consumption of alcohol (particularly the increase in consumption of wine in pubs and restaurants) and aims to use neural network image recognition of socal (e.g.: Instagram) images into the future to dynamically model risk factors around the app user. * The data that we have brought together is difficult to join and blend in a meaningful easy to use way, but by starting at the audience benefit of safety information, spatial awareness and the ability to make data aware choices it betters their ability to enjoy their lives, with knowledge of past and predicted future safety values in and around where they are living their lives, socialising or commuting. * Data @ Heart team has particularly enjoyed using our knowledge to make this blended weighted decision tool for all members our community. https://public.tableau.com/profile/tones#!/vizhome/CrimeByPostcode1995-2017WithSocialPostOverlaid/CrimeByPostcode1995-2017WithSocialPostsIncidences?publish=yes https://public.tableau.com/profile/tones#!/vizhome/CrimeByPostcode1995-2017WithSocialPostOverlaid/CrimeByPostcode1995-2017Categories?publish=yes https://public.tableau.com/profile/tones#!/vizhome/CrimeByPostcode1995-2017WithSocialPostOverlaid/SocialPostsofCommunityReportsPotentialWarnings?publish=yes * Joining BOCSAR crime data (22 years data across NSW postcodes) with layers of geolocated, time-filtered social posts, (Twitter, Instagram and Facebook) that have been publicly posted and pinned, we process these for NLP semantic and entity understanding, in order to predict and offer insight to users of our app. The crime is split into 17 major categories which would work as user personalisation filters to tailor the experience to individual concerns. * We first gathered NSW police crime reports into a corpus of text data to train topic vectors which are then matched in closeness values to identify suitable relevant social posts, that are geolocation enabled, mapped in the area that you are currently in. * The information of trend predictions of crime in locations around where they are, helps better inform them of the risks that might be experienced. This is particularly important given the #MeToo movement and tragic circumstances experienced by the likes of Jill Meagher and Eurydice Dixon, as well the alcohol related “king-hit” punch crimes that ended in the tragic death of Daniel Christie. * This too, would help utilise police resources patrolling areas of predicted high crime areas based on our modelling calculations in a simple to use easy to access app on a smartphone. Our layers of geolocation mapping also blends and calculates the location of pubs and restaurants to weight the variables of incidence of crime, due to such factors of alcohol consumption. The data from AIHW has added the ability to incorporate trends and predictions from consumption of alcohol (particularly the increase in consumption of wine in pubs and restaurants) and aims to use neural network image recognition of socal (e.g.: Instagram) images into the future to dynamically model risk factors around the app user. * We identified a particular growth recently in the occurrence of transport related crimes in the 22 years of BOCSAR data and so would plan on building into the distance weighting of risk value to the users current location, further factorisation of key train stations and transport hubs where crime incidents have occurred. * The data that we have brought together is difficult to join and blend in a meaningful easy to use way, but by starting at the audience benefit of safety information, spatial awareness and the ability to make data aware choices it betters their ability to enjoy their lives, with knowledge of past and predicted future safety values in and around where they are living their lives, socialising or commuting. * Data @ Heart team has particularly enjoyed using our knowledge to make this blended weighted decision tool for all members our community. # Structural Topic Model Project - Crime Data # Sarah Fawcett + Tony Nguy # 07/09/2018 library(stm) library(igraph) library(stmCorrViz) library(tidyverse) library(dplyr) library(stringr) library(tidytext) library(car) library(reshape2) library(lubridate) library(ggpmisc) # Set working directory setwd("~/Documents/DATA-SCIENCE/GOVHACK/DATA") # Clean Out Old Objects rm(list = ls()) rm(Crime_95_17_wide) # 1: INGEST (PROTOTYPE) Crime_95_17_wide <- read.csv("Crime_Postcode_Data_1995_2017.csv", header=T) # Convert to Long Format Crime_95_17_long <- melt(Crime_95_17_wide, id=c("Postcode","Offence.category","Subcategory")) Crime_95_17_long_date <- melt(Crime_95_17_wide, id=c("Postcode","Offence.category","Subcategory")) # 2: PREDICT # Test of factor class(Crime_95_17_long$variable) # Convert Data to Date If Necessary # mdy(Crime_95_17_long$variable) Crime_95_17_long$variable <- as.Date(Crime_95_17_long$variable) Crime_95_17_long$variable <- as.factor(Crime_95_17_long$variable) # Convert Postcode to Character class(Crime_95_17_long$Postcode) Crime_95_17_long$Postcode <- as.numeric(Crime_95_17_long$Subcategory) Crime_95_17_long$Postcode <- as.numeric(Crime_95_17_long$Postcode) Crime_95_17_long$value <- as.numeric(Crime_95_17_long$value) # Generalised Linear Regression Model attach(Crime_95_17_long) model.glm.crime <- glm(Crime_95_17_long$Postcode ~ Crime_95_17_long$value + Crime_95_17_long$Subcategory + Crime_95_17_long$variable) # Summary model.lm.internet # Pedict predict.glm(model.glm.crime, data.frame(value=30, Subcategory=71, variable=21017, type="response", interval="confidence")) detach(Crime_95_17_long) # WRITE write.csv(Crime_95_17_long_date, file = "~/Documents/DATA-SCIENCE/GOVHACK/DATA/Crime_95_17_long_date.csv", row.names=FALSE)
Way 2 school of your choice We R - IIBIT Adelaide 5 8 This app gives a detailed information about school where parent can filter the options according to their need. So, the app provides information about list of schools with the details like location, enrolment dates, principal contact details, previous complaints on school, facilities for disability, school ranking, bus transportation, reviews about school (both positive and negative), facility for kids (activity room, library, play room). The second feature we can say is to provide access facilities, car parking facilities, bus transport and general road traffic volume near the school. This enables the parents to save their precious time, as we know parents have their jobs. will be included. Adding more to the benefits, we will list the data sets used by the project below.
Weather2Go YCY Brisbane 4 6 # Weather2Go Description We designed an App for weather. It informs the users how to do with the incoming weather, make them understand weather and change their behaviour for better health. ## Problem Space ### 1. Who cares about UV? - People always ignore the harmful weather Some weather is very harmful to people’s health, for example, UV from the sun. Excessive UV will greatly increase the risk of skin disease. Actually, everyone knows this fact, but people just ignore it because the bad results always come later. Appeals have been made from times to times, but they might only work for a short period. There should be an effective way to inform people about the risk and even change their behaviour. ### 2. I forgot my umbrella again! - The weather notification system is not smart We are busy. How can we remember to check the weather forecast every time before going out? Spend 50 seconds or more to open the browser and wait for google feed? Download an App and forget it in the third day? These are not going to solve the problem. A smart way is needed to make people know the weather without extra interactive workload. ### 3. Who knows what 23 degree means? – The weather information is not reported in a user-centred way. The weather data can be very unfriendly to general people. They always find it hard to relate a number value to a sense. In terms of UV, temperature and humidity, a user-centred way should be found to represent that information so that people know how to deal with the weather. ## Solutions and Features ### 1. Weather and alarm We came up with a good way to make people know the weather when they are going to attend some activity. Firstly, there is a notification pop when you should prepare something for the weather. Secondly, we combine the alarm clock into the app. ### 2. Realistic interaction makes behaviour into a habit. In the home page, users can see a character and the weather today. If it is going to rain, users are driven to hold a small umbrella with a special interaction for the character. If the sun UV is strong, the user will open a sunscreen and apply it to the body with fingers. By doing this, the interaction goes every deep into people’s memory so that taking the umbrella or using sunscreen is hard to forget. ### 3. Human-centred weather forecast We believe displaying the information in a way people are easy to understand is vital. In the home page, we tell the user toady’s weather and more importantly, we tell them how much it is colder or hotter than yesterday, how much it will increase skin disease risk if exposed to the sun for a different length of time, what to wear and what sport or activity is recommended. We even made a function for users to measure the UV damage. By rotating a clock, users will see visually how the skin changes from 20 minutes to 3 hours and how the disease risk increase based on the UV of that day. Since people see the future result and do an interaction to this, the chance they will use sunscreen is larger. Another example is we have a visual weather map in the app. Only knowing the weather in the different city is not the way how people understand the world. A weather map also provides useful information when people are about to do travel. The liner weather change can be displayed geographically. ### 4. Emotional designs We have many details that are designed to affect users’ emotion. These are important because human is emotional animals. It is easier to affect and control them with emotional elements rather than since fact or informative text. For example, the character is representing the user. His/her face and mood will change according to the weather and how the user treats the weather. In the weather map, users’ parents, lover and friends are showing along with the weather in their locations. Seeing those users can send small gifts like an umbrella or sunscreen to them to show their caring. Even we are far away, the love never changes. # Bureau of Meteorology We used data here for all the information in different locations including recordings and forecast. We did with the data in different ways. For example, compare the data with and analyse the change, relate the UV data to a disease data and change the usual styles based on weather data values. # # Australia Institute of Health and Welfare Relating the skin disease data with UV degree data, we will illustrate the risk of sun UV harm to the skin in a creative way and predict the incoming damage. People will be aware of the importance to do skin care. Apart from that, influenza and pneumonia is also a big concern associated with weather. It is useful for the daily suggestion about clothing. # Participation in Sport and Physical Recreation From people's sports preference we know what people would like to play. Then we can give appropriate sports suggestions based on weather condition data. With data from sports, the recommendation of activities is always from the top of what are popular.
Weather Intelligence Solutions Team Outliers Adelaide 9 22 Are the smart decision-making tools that Businesses and Government use are Smart Enough? Outliers is a team of Smarts from the Smarts. We provide insights to various industries all over the globe and facilitate Data Driven Weather Intelligent decision making. We achieve this by using Inter-Disciplinary perspective i.e. combining two or more very different concepts and creating an innovative idea, merging and manipulating unstructured data sources from various departments and including a component of weather patterns in our decision making. Here are few examples where we offer help to various industries: 1. Disaster Management: Weather intelligent Disaster Management Engine (WID-ME) enables disaster management team to predict and monitor real time disasters. WID-ME also incorporates weather intelligent machine learning capabilities to predict the possible events and envision customised Strategic Plans to help Disaster Management Teams and the Local Citizens to evacuate to a safer place. 2. Advertisements: Weather intelligent Advertising Tools help businesses target ‘Right Audience’ at the Right Time, Right Place and with Right Technology or Medium. This helps advertisers to optimize the cost on advertisements and improves ROI (return on investment). 3. Health-Care: Weather intelligent Alert System helps the businesses in healthcare industry as well as local population. Using machine learning tools, previous records of illness and mapping that to weather conditions, the system predicts the possible outbreak of a disease and generate alerts. This helps businesses to plan up with their manufacturing and supply of various drugs. This also helps users to contact specific and specialised doctors when needed. 4. Similarly, we work with other industries like Sports, Transportation, Adventure, Agriculture, Food, Construction, Power and many more to help them with various Data Driven Weather Intelligent solutions. Also, the maintenance of public services can be facilitated by the weather driven intelligence. WID-ME: A Complete Support System for Disaster Management WID-ME is one of the most advanced, innovative and simple tools that eases and advances the Disaster Management in Australia. With advance technology WID-ME ensures precise and accurate disaster prediction, anticipation of the situation using International weather data and builds an automated situation specific action plan. Assumption: 1. The weather data is globally available for us to use. 2. We have real time weather data available. 3. We have the details for alerting citizens. WIDME uses the real-time weather dataset and the dataset from various departments like BOM, to monitor and detect the disasters like fire outbreaks. Using the demographics and resources like hospitals, schools and reservoirs, WIDME provides personalized strategic plans to the citizens as well as the CFS. The citizens get alert to relocate to nearby safe places. The CFS also receives plans about the resources available and their locations to assist the citizens in their evacuation plan. Using real time monitoring, WIDME detects the possible area under threat, so that the CFS can focus on that particular area and supress the fire as early as possible. This support system integrates data sources like: 1. Weather condition and Weather Predictions using International weather data 2. Past Disaster History 3. Location, Population and People Demographics 4. Resource Location [Hospitals, Schools, Dams or other water bodies, Fire Brigade etc.] 5. Government marked Safe and Dangerous location data 6. Alert and Contact details 7. Emergency Contacts List Refer to individual datasets submitted for more details.
Weather To Go Team 18 Sydney 6 5 Our team aims to provide a solution for public transportation challenges that Sydney is facing. According to the data provided by BOM and Open Data, there is an obvious correlation between weather, and busses or trains punctuality and high usage volumes. We have prepared the “Weather to go” software: a two-part solution to help out both the users and the public transportation officers. Users can connect to the chatbot that analyzes the real-time data around the user like weather and the traffic intensity, and helps to decide what is the most optimal time to leave for the bus or train. The dashboard is our future feature, that could provide the recommendations for the governmental agencies. It would include the real-time data about the capacity, weather, and traffic. All data would be provided in easy to use, interactive graphs. In that matter, the “Weather to go” could be a great help in planning, developing and improving the NSW public transportation. As part of the research for our project, we verified whether there was a correlation between bad weather and transport delays based on historical data in a scientific way. We combined data about Transport for NSW Public Transport Patronage, Sydney trains performance and Bureau of Meteorology climate statistics from the same time period 2011-2018, and use the time series as the common reference to create the rain and transportation relation graph. For the bus data, we calculated the average punctuality percent from all bus companies in the same day to get more accurate punctuality rate. This data will be used for our Weather to go forecasting dashboard to generate predictions based on historical data. Under the hood, the Weather to go chatbot is using Bureau of Meteorology - Latest Weather Observations for Sydney - Observatory Hill dataset, along with Transport NSW Roads Real Time API and Transport NSW Realtime Trip Updates API for the chatbot real time updates functionality to enable consumers to have more data to make better transport decisions.
WeatherWizard Team 8 Sunshine Coast (USC) 5 0 By using Rainfall Data, Tourism data and Weather Data we have created a program to find the best tourism location based on the season and data for the best experience, increasing tourism on the coast.
Where Can? Battlerz Melbourne 3 11 Provide a free market research tool for SME's on public data sets A SME wants to open a new gym in North Melbourne, does not have the funds to do a full market research. WhereCan? can help the entrepreneur with a quick analysis of public data to help make data driven decisions on key aspects like the business-location-fit, competitors and potential partnerships in the area
Where the Peeps Team 347 Canberra 8 2 Building Wi-Fi usage heatmaps Trying to trace people's movements based on the access points they connect to. We began by looking at the University of Canberra Wi-Fi usage dataset. We found it interesting that you could associate the user id with the usage data. We explored usage data for all of Canberra and we found that it was very de-personalized, very 'big picture'. We couldn't use it to tell stories about individual users. We thought if we demonstrated something amazing we could make with the more detailed University of Canberra dataset, then that would give more incentive to add fields such as user ids to the overall Canberra Wi-Fi usage data. We would use UC as a proof-of-concept for our user-tracking idea and see if we could create a business case for collecting more detailed user Wi-Fi activity for the rest of Canberra.
Wynbus Wynners Wyndham 4 4 Point Cook has been one of the fastest growing suburbs in Australia, but has limited bus coverage. This is similar case across multiple areas in Wyndham and other growth areas across Victoria. PTV revises bus routes and introduces new routes on a regular basis, but the coverage of bus routes for new estates and the frequency of buses is inadequate and has not been revised frequently. This project proposes a pilot On-demand Flexi Public Transport Solution for areas/routes with poor bus coverage within Wyndham , whereby members of public can avail membership based "On-Demand", Flexi Public Transport services in Wyndham. Considering challenges with bus connectivity for growth areas like Point Cook, there is priority support required from PTV. This “WynBus” projects supports PTV with required data to support their business case for new routes. This also can be considered as a pilot project by PTV which can be progressively introduced in new growth areas by PTV to test new routes before actual route changes. Till PTV bus routes are in place, this project helps the local community to work together as a team and support the public to use public transport and reduce dependency on cars and station car parks. Point Cook has been one of the fastest growing in Australia with 250% population increase in the period 2006-2016, witha further increase of 15.4% (8,151 people) in the past 2 years. Population is expected to increase further by~30% in the next 21 years. SOURCE: HTTPS://PROFILE.ID.COM.AU/WYNDHAM/POPULATION?WEBID=120&ENDYEAR=2006&DATATYPE=UR Due to lack of local jobs, approximately 62% of the workers work outside of Wyndham area. Source: ID.com Considering the high population growth and lack of local jobs and poor road infrastructure, public transport is an important keyinreducing traffic congestion. However, the public transport access is currently inadequate and is failing to keep up with the growth here in the growth areas of Wyndham which includes Point Cook. Source: https://atlas.id.com.au/wyndham The number of people using cars for transport has increased by 12000 which compares with the additional 6000 people who are using trains in 5 years (2011-2016), which again highlights the lack of public transport. Note: Williams landing was opened on April 28, 2013. The coverage of bus routes for new estates has not kept up with our growth with reviews of service provision not keeping up with the demand. The routes were last updated in August 2017 and due for revision in Dec’2018 according to an update in from PTV website. Economically disadvantaged People/ Senior Citizens/School Kids/Youth with less access/no access to cars are forced to walk for miles/spend hours waiting for connecting buses/trains to reach to key spots within Wyndham from Point Cook • No directbus access from Point Cook to Aqua pulse/Encore Centre or the Eagle stadium for participating in swimming classes and indoor sport activities • No direct bus access to the regional shopping centre of Pacific Werribee and our local cinema. • Our bus routes are to train station dependent. You cannot get to the Point Cook Town centre from Sanctuary Lakes without 2 buses and a short walk. • Frequency of buses is very poor and does not align with the school times so that parents are heavily dependent on driving them to school. As a result of this, a family travelling to Aqua Pulse from Point Cook or a young student working part-time in Pacific Werribee might have to spend ~1.5hrs -2 hrs. one way in public transport instead of 15-20 minutes in car.
WynOverTraffic Transformers Wyndham 1 0 This project is to analyse Wyndham's traffic data related to accidents. The project is to provide insights to the given data and provide probability of likelihood of accidents across different parameters. The purpose is to enable Wyndham to prepare, prevent and progressively eliminate the accidents in Wyndham roads.
WynTeleSmart TeleSmart Melbourne 3 7 Growing Wyndham may witness huge growth in citizens living alone or aged persons above age of 65 years. Our project analyse this situation and gives an IOT & telecare based smart home solution to address such issues 1. Growing aged population of Wyndham City analysis 2. Forecast household types - Lone person households analysis 3. Forecast household types - One parent family analysis 4. 10 Dangers of Seniors Living Alone 5. Wyndham City Council should add Telecare service as service offerings 6. Description of Telecare 7. Architecture diagram of Telecare 8. Solution Proposed
Xtra Jobs XTRA Adelaide 9 20 Problem The number of unemployed people in South Australia is quite high. South Australia has the highest rate of unemployment among all the states of Australia. One reason behind this is the problem coming from the jobs demands and supplies provided in South Australia. Sometimes, people’s skillsets do not meet the job criteria. Another reason is that a skill gap exists between professional skills and employable skills. As can be seen from most of the job advertisements; soft skills are needed but no particular methods to measure them exist. Whist universities, training centres and government agencies are providing services and degrees related to professional skills; recruiters are also looking for employable skills as well. The issue here is that while many people cannot get into the industry, recruiters find it hard to employ the right candidates. While the technologies keep changing, lacking these transferable skills will cause people soon unable to keep up with changes and switch paths. . Who Therefore, XTRA team comes up with an idea called Xtra Jobs which provides information about what skills are required through an interactive website and mobile application. The job seeking citizens are the target of the application. Recruiters and government agencies are users of Xtra Jobs as well. . Solutions (Features) 1. The content of the website/app includes various types of games to assess the soft skills of the users, and record user profiles. 2. The website/app will collect and store information about users and share to some companies/employers, where related, if user opts in. Additionally, in this application, users can get the information about what skills are required for particular jobs, where they can focus on developing specific skills. 3. A report of the user’s skillset can be generated for users to attach onto their CVs. 4. A record of this information will be used by universities, recruiters and government agencies to provide services and training needed for particular groups of people based on their interests or residents of certain areas. . How The skills assessment method is that, for a particular skill, there will be a unit to assess the level of user’s skill, ranking from 1 – 100. Users can get additional credit or increase their level by completing training and participating in some events provided by authorised organisations. These organisations will be given the authorities only from the Government. For example, a competitor attending GovHack will be given additional credit from the organisation on their team work, networking, communication, coding, leadership skills when they met the criteria provided by this organisation. The competitor needs to provide evidence to the organisation for the skillset if they want to get credit. GovHack will then be responsible as a referee when they are giving credits to the competitors. . Benefits The benefits of the application are: • For job seekers: this is good for self-improvement, strengthening their CVs by accessing information for different opportunities services and training provided. This is a way to be job ready. • For the employers and businesses: the application will provide them a list of skilled users and reduce the recruiting processes as there will be a way to measure the employable skills. • For universities: skill training centres, community centres, they can provide the essential training, services for a particular group of people and areas. • South Australia will have lower rate of unemployment. This helps reducing the applications and workloads at Centrelink. 1. Problem: 1.1. South Australia has the highest unemployment rate among all states in Australia. Even the employment growth is 51%, this figure is still under Australian employment growth average. 1.2. Recruiters are looking for degrees, experiences, employable skills. Employable skills make applicant stand out. However, employable skills are not measurable. 1.3. Most emphasised employable skills are: • Interpersonal & people skills • Communication & teamwork skills • Creativity & problem solving • Adaptability & resilience • Critical thinking • Reliability & motivation • Digital literacy . 2. Who: 2.1. Citizen job seekers 2.2. Recruiter 2.3. Universities, Government agencies, community centres, training centres . 3. Solutions: 3.1. Mapping professional skills and employable skills 3.2. Game based assessments 3.3. Increase credits by authorised organisations/companies/events with assessment criteria 3.4. Report of skills for individual to attach on CVs 3.5. Report for Government agencies, universities, councils -> which group of people and areas need special training, services. . 4. How: 4.1. Locations for training services: 4.1.1. Info from people with needs of particular skillsets 4.1.2. Location with high unemployment rate in South Australia 4.1.3. Populous location 4.1.4. Local government areas 4.1.5. Young residents (Aged from 18 – 35) 4.2. Events/programs training for some skillsets: 4.2.1. GovHack: 4.2.1.1. Communication & teamwork skills 4.2.1.2. Creativity & problem solving 4.2.1.3. Digital literacy 4.2.2. Toastmaster: 4.2.2.1. Interpersonal & people skills 4.2.2.2. Communication & teamwork skills 4.2.3. Working experience: 4.2.3.1. Communication & teamwork skills 4.2.3.2. Creativity & problem solving 4.2.3.3. Adaptability & resilience 4.2.3.4. Reliability & motivation
Yerrabi data d00ds Canberra 9 3 Yerrabi is intended to encourage people to be more active by taking away reservations about convenience, challenge and timing. By utilising geospatial data supplied by the ACT Government in addition to crowdsourced data, Yerrabi allows Canberrans the option to either follow known trails or ’blaze their own trails’. Moreover, we hope that Yerrebi will further Canberran’s appreciation for our iconic bushland and that the tracks scattered around the ACT and surrounds will be utilised more. We want to make use of the data provided by the ACT Government in a way that everyday Canberrans can easily access and utilise while simultaneously creating a product that promotes fitness and wellbeing.
YourATO TaxTransformers Wyndham 1 0 The project is to provide solutions for ATO to support and serve the people in need in lodging tax returns. This project also applies machine learning and artificial intelligence in providing better solutions using XGBOOST. https://data.gov.au/dataset/ad383be7-4666-4bbb-bfd0-9fffb374beff/resource/f3bcbd38-b3e9-4a27-8729-2314f05a6ae4/download/atoabsgovhack2018.xlsx from open dataset from ATO for this hack. This contains ATO, ABS and ABS-SEIFA details for years 2006, 2011 and 2016. Also, it has count of tax help centres at postcode level for the year 2018.
Your Local Council Team 180 Melbourne 5 7 Based the large number of free wi-fi hotspots (either at train stations, or at council locations) across Melbourne, this presents a unique opportunity to present those who connect with a data-driven story available in multiple languages. Given the geo-location of available wi-fi hotspots, users would be offered a chance to experience the history, demographic breakdown of the area, as well as local council information. We found that the data for councils can be very spread apart, across multiple sources (websites, reports, databases), and there is no easy method for residents or visitors to an area to find relevant information without attempting to search and filter through traditional channels. Our idea is that we could combine relevant data together, and present it to people in a familiar format, but through a unique method. With this idea/approach in mind, this solution concept collated information in various datasets from Kingston City Council, as well as the Trove database, KnowYourCouncil website, Census data between 2001 and 2016, and a combination of location datasets for Hospitals, Sports Grounds, and Schools. Based on this approach, we for-see this as a means to promote collaboration of open-data resources between local councils and to be something that could be easily adapted and utilized at both city (Wydnham) and state levels.