Artificial intelligence for waste management in smart cities: a review

Bingbing Fang, Jiacheng Yu, Zhonghao Chen, Ahmed I. Osman *, Mohamed Farghali*, Ikko Ihara, Essam H. Hamza, David W. Rooney, Pow-Seng Yap*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

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The rising amount of waste generated worldwide is inducing issues of pollution, waste management, and recycling, calling for new strategies to improve the waste ecosystem, such as the use of artificial intelligence. Here, we review the application of artificial intelligence in waste-to-energy, smart bins, waste-sorting robots, waste generation models, waste monitoring and tracking, plastic pyrolysis, distinguishing fossil and modern materials, logistics, disposal, illegal dumping, resource recovery, smart cities, process efficiency, cost savings, and improving public health. Using artificial intelligence in waste logistics can reduce transportation distance by up to 36.8%, cost savings by up to 13.35%, and time savings by up to 28.22%. Artificial intelligence allows for identifying and sorting waste with an accuracy ranging from 72.8 to 99.95%. Artificial intelligence combined with chemical analysis improves waste pyrolysis, carbon emission estimation, and energy conversion. We also explain how efficiency can be increased and costs can be reduced by artificial intelligence in waste management systems for smart cities.

Original languageEnglish
Number of pages31
JournalEnvironmental Chemistry Letters
Early online date09 May 2023
Publication statusEarly online date - 09 May 2023


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