Artificial Intelligence: How AI Makes Waste Management Forecasts Easier
Researchers at the University of Johannesburg found AI beats Excel at forecasting solid waste volumes and landfill requirements.
Cities across the world are grappling with the problem of finding landfill sites and new land as solid waste tonnage rises with population and economic growth. How does one forecast, over the long term, solid waste volumes and landfill requirements? AI could be the answer to the problem. (Eurekalert)
Dr. Olusola Olaitan Ayeleru and Mr. Lanrewaju Ibrahim Fajimi, researchers at the Department of Chemical Engineering at the University of Johannesburg, conducted a study to demonstrate whether AI could more efficiently provide city waste managers with the data and projections to address the issue.
AI to help manage waste
Spreadsheets have limitations in waste projections. They are hard to understand because they need to build in macros and formulas. It is also difficult to conduct scenario analysis with spreadsheets, as also is accounting for data such as population growth, waste types, weather, and other variables.
Another problem is the paucity of full data, particularly in developing countries.
The city of Johannesburg received a wake-up call in September 2020 when the COO of Pickitup, the city’s waste management company, warned that only four and a half years of capacity was left at the city’s four landfill sites.
Fajimi deployed AI to analyze the city’s waste problem. He found that a 10 neuron artificial neural network, an AI model that could learn from new data, produced the best forecasts.
The 10-neuron model forecasted that the population in Johannesburg is likely to increase from 5.3 million in 2021 to 6.4 million in 2031, and to 8.4 million in 2050.
It also forecasted an increase in total annual waste from 1.61 million tonnes in 2021 to 1.72 million tonnes in 2031, and to 1.95 million tonnes in 2050.
“The City of Johannesburg is currently doing much better in its waste management compared to other large cities on the continent. This AI forecast can help facilitate the city’s design of future waste management infrastructure,” says Ayeleru.
“In the short term, the first step the city can take is educating people, so they start recycling more. Secondly, the city may need to look beyond what they are doing at the moment to generate income from solid waste.”
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