Waste:ED

Project Info

Noosa Waste Management thumbnail

Team Name


Noosa Waste Management


Team Members


Daniel and 1 other member with an unpublished profile.

Project Description


Educating the community about waste management and resource recovery, and encouraging more mindful behaviour through AI based reward or penalty systems. The goal is a long term reduction in waste to landfill through better community engagement from government provided waste collection services.


Data Story


Using address related GIS data and collection schedules, create an app that alerts users to the time and type of collection, while providing volume over time details of their waste production and resource recovery efforts to date, aggregated with local, regional and national level sources to paint a picture of everyone's combined efforts.
Use AI to "score" and/or categorise contamination in recycling bins, then use A/B testing of reward vs penalty based systems to encourage behaviour changes and reduce waste to landfill over time.
Additional features allow a barcode scanner in the app to determine if a product package is recyclable or not


Evidence of Work

Video

Homepage

Project Image

Team DataSets

SoE2017: Household waste recovered or recycled

Description of Use Research

Data Set

SoE2015: Per capita waste generation

Description of Use Research

Data Set

SoE2017: Interstate household waste received

Description of Use Research on out of state imports

Data Set

Materials recovered - 2015

Description of Use Research on waste recovery

Data Set

Public waste and recycling facilities in Queensland

Description of Use Direct end users to waste collection facilities from within the App

Data Set

Trends in domestic kerbside waste 2007-2014

Description of Use Research

Data Set

Ballarat bin lifts by truck

Description of Use Daily activity of bin trucks, showing time of collection and daily duties

Data Set

Ballarat bin lifts

Description of Use Daily activity of a waste collection service for LGA

Data Set

Ballarat waste volume

Description of Use Waste volume produced for LGA - competitive comparison

Data Set

Sunshine Coast - Bin colleciton days by street

Description of Use Lookup location and report on bin collection type and day of week

Data Set

Challenge Entries

Increased participation in Plastic Free July

People are increasingly aware of the problems with plastics and want to ‘do their bit’ but how do we increase engagement in Plastic Free July? Using data and IT-based solutions, how can we increase both geographical update and reach a wider demographic (particularly more men)?

Go to Challenge | 18 teams have entered this challenge.

Training AI models to deliver better human outcomes

For an outcome create two AI models based on contrasting incentive systems and examine the differing impacts on the defined outcome.

Go to Challenge | 12 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.

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.

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.

🌟 Community “Clean, Green and Lean” Rewards

Develop a business solution which encourages people to live an active and green lifestyle, incentivised by a digital perks system, offered in partnership with local businesses.

Go to Challenge | 15 teams have entered this challenge.

🌟 Creating a clean city

Our residents and businesses produce, consume, and dispose of waste every day. Many residents are unaware of what happens to their waste once it enters a bin or simply don't care. How might we use data to empower and educate our community about their waste?

Go to Challenge | 12 teams have entered this challenge.

The best use of Gold Coast Data

Best use of Gold Coast Data

Go to Challenge | 8 teams have entered this challenge.