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Artificial intelligence for waste management in smart cities: a review

Authors :
Bingbing Fang
Jiacheng Yu
Zhonghao Chen
Ahmed I. Osman
Mohamed Farghali
Ikko Ihara
Essam H. Hamza
David W. Rooney
Pow-Seng Yap
Source :
Fang, B, Yu, J, Chen, Z, Osman, A I, Farghali, M, Ihara, I, Hamza, E H, Rooney, D W & Yap, P-S 2023, ' Artificial intelligence for waste management in smart cities: a review ', Environmental Chemistry Letters . https://doi.org/10.1007/s10311-023-01604-3
Publication Year :
2023

Abstract

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.

Details

Language :
English
Database :
OpenAIRE
Journal :
Fang, B, Yu, J, Chen, Z, Osman, A I, Farghali, M, Ihara, I, Hamza, E H, Rooney, D W & Yap, P-S 2023, ' Artificial intelligence for waste management in smart cities: a review ', Environmental Chemistry Letters . https://doi.org/10.1007/s10311-023-01604-3
Accession number :
edsair.doi.dedup.....19d6167639da3586240f373bf5f8881d
Full Text :
https://doi.org/10.1007/s10311-023-01604-3