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
Evidence of Work
Kerbside Collection Data
Description of Use: It enables us to sort by a combination of waste material, council area and year, providing a graphical presentation of location and trends.
Description of Use: Population forecast is taken to analyse the impact of population induced waste will have when there are fewer landfills to accommodate them. Population experts, .id analyse and convert the raw figures from ABS into stories of place to inform council staff, community groups, investors, business, students and the general public.
Australian Bureau of Statistics
Description of Use: True raw source of data for demographics, social atlas, unemployment rates, average weekly earnings per gender, age group etc.
Description of Use: he maps are shaded to show where there are concentrations of these communities of interest, which enables planners to accurately assess the demand for the provision of services and facilities to target populations. The thematic maps are created using data from the 2016 and 2011 Censuses of Population and Housing, with an option to view the data for the 2016 year, the 2011 year, or change in number or percentage between the two Censuses. Tables, charts and concise factual commentary are also available from the ‘Analysis’ tab, for each Census year individually (not for the change).
Annual Waste Report - Victorian Councils
Description of Use: This data will be correlated with the ATO, ABS, Socia Atlas, Population density, Economic profiles to strategize the Education, Engagement, Measurable activities the council can target with specific groups of communities where the waste management is not optimal.
Description of Use: This data will be used to decide the rewards that the council will offer for best waste management practices. The reward will pro-rated based on the income levels of the user/user-groups.
ATO Data set
Description of Use: This data will be used to correlate the demographic profiles and the diversion rates of the waste produced by specific households.
De-indentified Individual ATO statistic data
Description of Use: This data will be used to reward individuals following best waste management practices. The data here will be collated with the waste management data gained from their daily use.
Description of Use: How to effectively deal with Biomass to ensure the energy produced by the waste is used effectively to run other utilities like power.
Waste Management Strategy - Casey Council
Description of Use: Identify the best practices and the strategy for waste management planned by Casey council. This paper laid the groundwork to identify the best practices to plan for given the landfill location constraints.
ABN Bulk Extract
Description of Use: This data will be used correlate commercial companies tax returns and their waste management data to decide on rewards or recognition's for best practices in waste recycling.
Check back here once the first checkpoint passes to see the challenges this team has entered.