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Artificial intelligence for waste management in smart cities: a review
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...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10169138/ https://www.ncbi.nlm.nih.gov/pubmed/37362015 http://dx.doi.org/10.1007/s10311-023-01604-3 |
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author | Fang, Bingbing Yu, Jiacheng Chen, Zhonghao Osman, Ahmed I. Farghali, Mohamed Ihara, Ikko Hamza, Essam H. Rooney, David W. Yap, Pow-Seng |
author_facet | Fang, Bingbing Yu, Jiacheng Chen, Zhonghao Osman, Ahmed I. Farghali, Mohamed Ihara, Ikko Hamza, Essam H. Rooney, David W. Yap, Pow-Seng |
author_sort | Fang, Bingbing |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10169138 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-101691382023-05-11 Artificial intelligence for waste management in smart cities: a review Fang, Bingbing Yu, Jiacheng Chen, Zhonghao Osman, Ahmed I. Farghali, Mohamed Ihara, Ikko Hamza, Essam H. Rooney, David W. Yap, Pow-Seng Environ Chem Lett Review Article 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. Springer International Publishing 2023-05-09 /pmc/articles/PMC10169138/ /pubmed/37362015 http://dx.doi.org/10.1007/s10311-023-01604-3 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Review Article Fang, Bingbing Yu, Jiacheng Chen, Zhonghao Osman, Ahmed I. Farghali, Mohamed Ihara, Ikko Hamza, Essam H. Rooney, David W. Yap, Pow-Seng Artificial intelligence for waste management in smart cities: a review |
title | Artificial intelligence for waste management in smart cities: a review |
title_full | Artificial intelligence for waste management in smart cities: a review |
title_fullStr | Artificial intelligence for waste management in smart cities: a review |
title_full_unstemmed | Artificial intelligence for waste management in smart cities: a review |
title_short | Artificial intelligence for waste management in smart cities: a review |
title_sort | artificial intelligence for waste management in smart cities: a review |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10169138/ https://www.ncbi.nlm.nih.gov/pubmed/37362015 http://dx.doi.org/10.1007/s10311-023-01604-3 |
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