Emergency Planning and Response
How can we better plan and respond to emergencies?
Go to Challenge | 5 teams have entered this challenge.
Weather Intelligence Solutions
Project Info
Team Name
Team Outliers
Team Members
8 members with unpublished profiles.
Project Description
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.
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).
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.
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.
Data Story
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.
Team DataSets
Power and Energy data (Australian Energy Statistics)
Description of Use Could be an attribution to the commonwealth of people.
Digital Elevation Model (DEM) of Australia derived from LiDAR 5 Metre Grid WCS
Description of Use Digital Elevation Model (DEM) of Australia could help us track possible flood with ground water data.
Residential Dwellings: Values, Mean Price and Number by State and Territories
Description of Use The residential price index could be affected by the possible emergency index.
Watercourse
Description of Use Help determine the logical dam break area.
Average Household Size
Description of Use We could use the average household size data to give information about the disaster which has influences on the supply and demand.
Vegetation land in Australia
Description of Use The vegetation land coverage could be used to monitor the higher risk of bushfire in a drier weather.
Temperature data
Description of Use We utilize the temperature datasets from the BOM and combines other datasets related to the disasters pattern and other indicators to support agencies to better make risk management with combined information. (Eg. Higher temperature + low humidity + high vegetation coverage = high risk of bushfire)
SA Public and Private Acute Hospitals Locations
Description of Use The dataset is used to combine with the bushfire data, road data and climate data for agencies to lower the cost of human life when a disaster happens.
Global climate data
Description of Use We utilize the datasets from the Department of Environment and Waters and combines other datasets related to the disasters pattern, the public assets, the roads, and other indicators to support agencies to better make risk management and resource distribution with combined information.
Ocean data (Bureau of Meteorology)
Description of Use We combined ocean data with temperature data, rainfall data, climate data and etc. to provide insights to monitor ocean condition and the commonwealth of the citizens who live near the ocean or people whose living depends on the ocean condition.
Road data
Description of Use The road data is combined with climate and disaster datasets to help agencies evacuate or manage resources efficiently under severe condition.
Conditions of major reservoirs (California)
Description of Use We utilize the conditions of major reservoirs data in California to provide risk management information for major agencies to help them come up with a better strategic plan for water distribution when a bushfire occurs (eg. bushfire could cause air pollution and water pollution).
California Wildfires (International)
Description of Use Knowing the location and extent of wildfire events that affect California may help resource managers predict and manage potential impacts burns may have on California's water quality (combined with the dam data), availability, movement and citizens' wealth.
MFB locations (Metropolitan Fire Brigade locations) data
Description of Use We utilize Metropolitan Fire Brigade location data combined with other datasets, such as bushfire data, solar data, humidity data and etc. to provide applicable information to multiple agencies and provide information such as the distance of the incident and the closest fire brigade location.
Assets at risk according to bushfire places
Description of Use We use assets at risks data combining with the bushfire data, the fire brigade location and water resource data from different councils to provide valuable information on bushfire risk management to the agencies in charge.
Bushfire Safer Places
Description of Use We utilize bushfire safer places data to provide information combined with the bushfire data, the water dam data, the population data and etc. to support agencies to make appropriate decisions when incidents like bushfire happen.
Groundwater Data (Standing water level and well location)
Description of Use The purpose of using the data is to monitor the standing water level and track the humidity of the soil. The combination of the groundwater data could not only use for disaster and damage monitoring, it could be used in our strategic plan to help the government agencies to come up with better construction plan(when, where and how), recovery plan, water allocation and etc. in various hazard conditions.
Daily rainfall data
Description of Use We use daily rainfall data to monitor the humidity, possible chance of flood, dam failures, and other disasters. Also, to provide a maintenance schedule for public facilities(eg. rusty facilities, equipment failures) to avoid public dangers by combining the data from different departments and collaborating together.
Population Density, Australia
Description of Use We use the Population Density dataset of Australia to see which places are more populated that should be taken care of carefully. And also to come up with an evacuation plan (merged with streets and roads map)to manage people's mobility when disasters happen.
Near-Surface Wind Speed
Description of Use We use the Near-Surface Wind Speed data to monitor the disaster. Such as if a bushfire incident is happening, we use the data to track the possible spreading speed of the bushfire.
The Angas Catchment Dams dataset
Description of Use We use the Angas Catchment Dam's dataset to monitor the water volume in the dam. We could use it for water resource management and emergency planning and response when a huge fire disaster happens or when there is a need to adjust the water volume.
Daily solar exposure data
Description of Use We use daily solar exposure data in the SA area to monitor the possibility of bushfire happening and related disasters. Eg. Under how long of daily exposure put people at the risk of bushfires?
Challenge Entries
Improving Response
Best entry that assists CFS planning for and responding to incidents.
Go to Challenge | 7 teams have entered this challenge.
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?
Go to Challenge | 20 teams have entered this challenge.
Exploring the Oceans
How can we use ocean data to better support decision making for how we use our oceans? What sort of information presentation could provide more effective understanding of ocean dynamics beneath the ocean surface over a period of time?
Go to Challenge | 9 teams have entered this challenge.
Your Friendly Council
How can councils collaborate and use information to deliver better services to communities across South Australia?
Go to Challenge | 11 teams have entered this challenge.
Transforming the national to the international (National)
Where should Australian Businesses go next?
Go to Challenge | 15 teams have entered this challenge.
Bounty: Mix and Mashup
How can we combine the uncombinable?
Go to Challenge | 61 teams have entered this challenge.
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?)
Go to Challenge | 24 teams have entered this challenge.
Better Services - Citizens at the Centre
How can we provide better services to South Australian citizens and businesses?
Go to Challenge | 17 teams have entered this challenge.