Team Name:
Tessellate
Team Members:
Tessellate
As we aim to take a proactive approach at preserving one of our most valuable resources, our environment, we turn to another valuable resource for solutions. Data. Our response to the current climate is to create an app we call Well Bee-ing, Powered by Open Data, tools, and individual actions.
The approach used by this app is unique in that it fosters change by elevating three types of power: whole power (connecting and magnifying strengths and resources across an entire system) Way power: developing specific pathways to reach a goal and make dreams a reality, and will power: through persuing goals through dedication and sustained motivation to achieve new possibilities.
Well Bee-ing also provides reference points for the individual and government to see progress in our ecological footprint, carbon emissions, air quality, water usage, and waste production. We do not know of other apps which connect individuals and government to work so dedicatedly on their ecological wellbeing.
We did analyses of multiple open data sts like City of Ballarat waste datasets. These helped us identify patterns waste production and enery usages. We build spatial visualisations for understanding where there are under-served areas for waste collection (e.g. public litter bins) and analysing trends in gross waste volume.
We used open tools like Ecological Footprint finder from World Wildlife Foundation and Water Wise from Water Corp
We built image classification AI / ML models to identify trash that can be recycled at home , trash like styrofoam that needs to go to recycle center and trash that cannot be recycled
Description of Use Data was used to create a Google Maps heatmap overlay of average pollution data, updated for time of day. Users are able to view the pollution heatmap for the current time overlayed on any directions they require and can then choose the route that exposes them to the least amount of pollution.
Description of Use Data used to create visualisations of waste collection trends over time for the City of Ballarat and extract insights around high volume periods.
Description of Use Provides an overlay of City of Ballarat waste collection zones for spatial analysis and comparison with waste collection heat maps.
Description of Use Localised analysis of landfill, recycling and green waste collection across City of Ballarat. Allowed for creation of heatmaps for where waste is collected from.
Description of Use More granular analysis of green waste collection in aggregate (not localised).
Description of Use More granular analysis of recycle waste collection in aggregate (not localised).
Description of Use More granular analysis of landfill waste collection in aggregate (not localised).
Description of Use Create a map overlap of the public (landfill) litter bins for the City of Ballarat. This overlay sits on top of other analyses of waste data for the area. This provides additional insight into areas that are more or less well-served in terms of waste disposal facilities.
Description of Use Challenges - Plastic Free July
Description of Use Challenges: - Plastic Free July
Eligibility: Use any open dataset to support your entry.
Go to Challenge | 18 teams have entered this challenge.
Eligibility: Use any open dataset to support your entry.
Go to Challenge | 45 teams have entered this challenge.
Eligibility: Use any open dataset to support your entry.
Go to Challenge | 15 teams have entered this challenge.
Eligibility: Use any open dataset to support your entry.
Go to Challenge | 32 teams have entered this challenge.
Eligibility: Use atleast 1 City of Ballarat waste dataset from data.gov.au
Go to Challenge | 12 teams have entered this challenge.
Eligibility: Must make use of any open dataset and apply two different incentive systems
Go to Challenge | 12 teams have entered this challenge.
Eligibility: Use any open dataset to support your entry and having experience in scientific visualisation
Go to Challenge | 11 teams have entered this challenge.
Eligibility: WA contestants only
Go to Challenge | 6 teams have entered this challenge.
Eligibility: Use any open dataset to support your entry.
Go to Challenge | 39 teams have entered this challenge.
