Quality Air

Project Info

Haxolotl thumbnail

Team Name


Haxolotl


Team Members


5 members with unpublished profiles.

Project Description


1 in 9 Australians suffer from chronic respiratory diseases, a group of conditions that have a wide range of triggers, including dust, pollutants, temperature, humidity and pressure. We wanted to design a tool for the community, but specifically targeting those with respiratory illnesses, that could help them navigate both living and travelling to other areas. Our solution is geared towards QLD but has the capacity to be expanded to other states and territories.

Our solution is a website called Quality Air, providing historical air quality information and live hourly updates for different regions of QLD. We have a home page with statistics concerning chronic respiratory conditions in Australia and serves to highlight the importance of why we created this website. It also shows our team, and a detailed explanation of the PM10 and PM2.5 air quality variables that we are focusing on and why they are a problem for those with respiratory illnesses.

We have analysed data and statistics for South Brisbane (a metro area) and Hopeland (a remote regional area). Each page has a satellite image sourced from Google maps, along with a description and statistics from the ABS regarding areas that affect air quality data, such as population density and the number of motor vehicles. We implemented a widget that updates the current weather forecast and other information. Monthly averages for variables that can affect air quality for those with chronic respiratory illness are included and sourced from the Bureau of Meteorology. Ideally, these variables would update each month. The PM10 and PM2.5 data for the month of June 2019 have been graphed to show the changes and fluctuations, with the averages listed and their corresponding rating from the Environmental Protection Authority. We also implemented an API which updates various air quality data including carbon monoxide, nitrogen dioxide, particle PM10 and PM2.5 values every hour in real-time.
We would like the capacity to have individuals who use this tool to create a profile. This would enable them to add their conditions. We are particularly focused on asthma and COPD (from AIHW data), but we could expand this to other illnesses such as inflammatory lung disease, bronchitis and upper respiratory infections. We have listed triggers specifically relating to environmental factors and air quality, and what PM these would fall into. It enables individuals to track variables that are relevant to them. Links to Institute of Health and government websites provide more information for individuals who use our website.

Those indicators can provide information on various places in Queensland and can help when planning to travel. Using historical air quality data in both regional and metro areas, individuals can plan their travel appropriately and medical action plans from GP’s can be tailored with a higher level of detail to individuals with more severe forms of respiratory illness. Our website helps could also help all users make informed decisions on visiting or moving to areas and could encourage migration to regional areas with less pollution.

The website presents a correlation between poor air quality and urbanisation, as well as the effect that dense populations have had on the environment. Our prototype website features example pages to compare data for a rural and an urban area – Hopeland and South Brisbane respectively, however we planned to expand the website to include all locations featured in the Queensland Government air quality API. We also planned to add customisable profiles and tailored recommendations to all pages, as well as take live data from BOM’s databases. The month-long graphs take data from the historical Queensland Government air quality recordings, and eventually we hope to automatically generate these graphs every day covering the last 30 days.

The purpose of the Quality Air website is to simplify complicated data, displaying specific values and making them more readable and accessible to the community. Having a tool like Quality Air to provide historical air quality data and live hourly updates would be invaluable for those with severe chronic respiratory conditions. It could assist in the management of respiratory illness and prevent hospitalisations.


Data Story


We compared Queensland Government air quality data from urban and rural areas over a one month period in order to emphasise the improved air quality in regional areas. Anomalous events such as bush fires and dust storms can skew data on PM10 and PM2.5 levels, so we limited our analysis to a one-month period to avoid anomalies. The rural areas particle levels were one third of the urban areas.

Our vision for the finished Quality Air website would automatically update the charts on particle levels daily, alongside more charts for all available air quality data. Real-time air quality data was taken from the Queensland Government's API. We included averages from the Bureau of Meteorology's weather data

  1. Data from BOM, data.qld.gov.au, ABS, census data and climate were looked into, including carbon monoxide, nitrogen dioxide, ozone and particulates
  2. Air quality monitoring data from the first 6-months of 2019 was selected. PM10 and PM2.5 were chosen to analyse.
  3. Graphs from June 2019 for South Brisbane (metro) and Hopeland (regional) were created and important values calculated
  4. Historical data for each place was researched
  5. Website was created using Google Sites
  6. Live air quality monitoring XML was coded and embedded into our website

Evidence of Work

Video

Homepage

Project Image

Team DataSets

Open Data Portal - Air Quality Monitoring Live data feed

Description of Use We took live updates on air quality from the xml api and published them on our website with a page for each location. Our website targets people with respiratory conditions that are triggered by different kinds of air pollution. We planned to have a full map of Queensland where users can select different regions and see data summaries based on their preferences.

Data Set

ABS Census

Description of Use Population data and number of motor vehicles

Data Set

QLD government - Download air data

Description of Use We used recordings of air quality over the past year to publish mock-up graphs showing data for the month of June 2019. We planned to have our website consistently update these graphs for the last 30 days across all recorded locations using this data. This also allowed us to compare pollution levels between a rural area (Hopeland, South West Queensland) and an urban area (South Brisbane).

Data Set

BOM Climate Data Online

Description of Use Our website targets people with chronic respiratory conditions, showing them live air data dependant on what factor might trigger their conditions. Along with pollution, some of these factors include humidity and pressure, so we used BOM data to show information about the weather in different locations, specifically South Brisbane and Hopeland.

Data Set

Challenge Entries

Highlighting the regional living advantages over metropolitan capitals.

Enabling people to choose the most suitable regional centre for a sea or tree change.

Go to Challenge | 11 teams have entered this challenge.

Spatial Information

How might Queenslanders find out more about where they live?

Go to Challenge | 19 teams have entered this challenge.

Queensland OpenAPI

Create a project using one or more of Queensland's Open-API’s

Go to Challenge | 39 teams have entered this challenge.

Thrive or survive: how can we adapt for the future?

What will Australia in 2050 look like?

Go to Challenge | 38 teams have entered this challenge.

Helping Start-ups and New Small Businesses in Australia

Choose one of the following questions to address: 1. What trends in business activity can help encourage self-employment through NEIS? 2. What type of NEIS businesses are being started and are successful (participated in the full 12 months of NEIS Assistance) and what can we learn from broader industry growth areas? 3. How do we encourage self-employment through greater participation in NEIS for cohorts currently underrepresented?

Go to Challenge | 21 teams have entered this challenge.

Reducing CBD Traffic Congestion

How to reduce traffic congestion or parking problems in CBD?

Go to Challenge | 39 teams have entered this challenge.

🌟 Pedestrian and Air Quality Sensor Data

How might we improve users’ experience of their city by using data from pedestrian and vehicle counters and/or air quality sensors?

Go to Challenge | 15 teams have entered this challenge.

🌟 Community open data weather monitoring and alerts system

Develop a digital solution, underpinned by IoT (Internet of Things) data, which is capable of early detection and alerting for weather and climate related risks to the community.

Go to Challenge | 10 teams have entered this challenge.

Public Transport for the Future

How might we combine data with modern technologies - such as AI/ML, IoT, Analytics or Natural Language interfaces - to better our public transport services. Outcomes could take the form of new commuter experiences, reduced environmental impact, or helping plan for the future.

Go to Challenge | 45 teams have entered this challenge.

Environment and Science Data

How might we use environment and science data to better engage with the community?

Go to Challenge | 19 teams have entered this challenge.