Artificial intelligence for waste management in smart cities: a review.

Autor: Fang B; Department of Civil Engineering, Xi'an Jiaotong-Liverpool University, Suzhou, 215123 China., Yu J; Department of Civil Engineering, Xi'an Jiaotong-Liverpool University, Suzhou, 215123 China., Chen Z; Department of Civil Engineering, Xi'an Jiaotong-Liverpool University, Suzhou, 215123 China., Osman AI; School of Chemistry and Chemical Engineering, Queen's University Belfast, David Keir Building, Stranmillis Road, Belfast, BT9 5AG Northern Ireland UK., Farghali M; Department of Agricultural Engineering and Socio-Economics, Kobe University, Kobe, 657-8501 Japan.; Department of Animal and Poultry Hygiene & Environmental Sanitation, Faculty of Veterinary Medicine, Assiut University, Assiut, 71526 Egypt., Ihara I; Department of Agricultural Engineering and Socio-Economics, Kobe University, Kobe, 657-8501 Japan., Hamza EH; Electric and Computer Engineering Department, Aircraft Armament (A/CA), Military Technical College, Cairo, Egypt., Rooney DW; School of Chemistry and Chemical Engineering, Queen's University Belfast, David Keir Building, Stranmillis Road, Belfast, BT9 5AG Northern Ireland UK., Yap PS; Department of Civil Engineering, Xi'an Jiaotong-Liverpool University, Suzhou, 215123 China.
Jazyk: angličtina
Zdroj: Environmental chemistry letters [Environ Chem Lett] 2023 May 09, pp. 1-31. Date of Electronic Publication: 2023 May 09.
DOI: 10.1007/s10311-023-01604-3
Abstrakt: 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.
Competing Interests: Conflict of interestThe authors have not disclosed any competing interests.
(© The Author(s) 2023.)
Databáze: MEDLINE
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