Municipal Solid Waste Management: A Review of Machine Learning Applications
This study comprises of an analysis of various Machine Learning (ML) algorithms for municipal solid waste management to enhance waste management procedures and reduce the adverse environmental effects. The increasing population has resulted in substantial environmental hazards due to increased waste...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2023-01-01
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| Series: | E3S Web of Conferences |
| Subjects: | |
| Online Access: | https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/92/e3sconf_icgest2023_02018.pdf |
| _version_ | 1797345284907335680 |
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| author | Pillai Kiran S. M L Sneha S Aiswarya Anand Arya B. Prasad Geena |
| author_facet | Pillai Kiran S. M L Sneha S Aiswarya Anand Arya B. Prasad Geena |
| author_sort | Pillai Kiran S. |
| collection | DOAJ |
| description | This study comprises of an analysis of various Machine Learning (ML) algorithms for municipal solid waste management to enhance waste management procedures and reduce the adverse environmental effects. The increasing population has resulted in substantial environmental hazards due to increased waste generation. Therefore, an effective waste management system with much more efficient and innovative waste management techniques is required to reduce the adverse effects that would occur due to the generation of massive waste. This study reviews various ML algorithms to automate and optimize garbage generation, collection, transportation, treatment, and disposal. To deliver and predict effective and precise waste generation, segregation, and collection forecasts, the system integrates multiple ML methods including decision trees (DT), k-nearest neighbours (KNN), support vector machines (SVM), random forests (RF), and clustering algorithms. |
| first_indexed | 2024-03-08T11:16:30Z |
| format | Article |
| id | doaj.art-6c38922a6faa4f2f9bb223cca14e2913 |
| institution | Directory Open Access Journal |
| issn | 2267-1242 |
| language | English |
| last_indexed | 2024-03-08T11:16:30Z |
| publishDate | 2023-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | E3S Web of Conferences |
| spelling | doaj.art-6c38922a6faa4f2f9bb223cca14e29132024-01-26T10:34:40ZengEDP SciencesE3S Web of Conferences2267-12422023-01-014550201810.1051/e3sconf/202345502018e3sconf_icgest2023_02018Municipal Solid Waste Management: A Review of Machine Learning ApplicationsPillai Kiran S.0M L Sneha1S Aiswarya2Anand Arya B.3Prasad Geena4Department of Electronic and Communication Engineering, Amrita Vishwa VidyapeethamDepartment of Electronic and Communication Engineering, Amrita Vishwa VidyapeethamDepartment of Electronic and Communication Engineering, Amrita Vishwa VidyapeethamDepartment of Electronic and Communication Engineering, Amrita Vishwa VidyapeethamDepartment of Mechanical Engineering, Amrita Vishwa VidyapeethamThis study comprises of an analysis of various Machine Learning (ML) algorithms for municipal solid waste management to enhance waste management procedures and reduce the adverse environmental effects. The increasing population has resulted in substantial environmental hazards due to increased waste generation. Therefore, an effective waste management system with much more efficient and innovative waste management techniques is required to reduce the adverse effects that would occur due to the generation of massive waste. This study reviews various ML algorithms to automate and optimize garbage generation, collection, transportation, treatment, and disposal. To deliver and predict effective and precise waste generation, segregation, and collection forecasts, the system integrates multiple ML methods including decision trees (DT), k-nearest neighbours (KNN), support vector machines (SVM), random forests (RF), and clustering algorithms.https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/92/e3sconf_icgest2023_02018.pdfmachine learningrouting optimizationmunicipal solid waste managementsegregationdisposal |
| spellingShingle | Pillai Kiran S. M L Sneha S Aiswarya Anand Arya B. Prasad Geena Municipal Solid Waste Management: A Review of Machine Learning Applications E3S Web of Conferences machine learning routing optimization municipal solid waste management segregation disposal |
| title | Municipal Solid Waste Management: A Review of Machine Learning Applications |
| title_full | Municipal Solid Waste Management: A Review of Machine Learning Applications |
| title_fullStr | Municipal Solid Waste Management: A Review of Machine Learning Applications |
| title_full_unstemmed | Municipal Solid Waste Management: A Review of Machine Learning Applications |
| title_short | Municipal Solid Waste Management: A Review of Machine Learning Applications |
| title_sort | municipal solid waste management a review of machine learning applications |
| topic | machine learning routing optimization municipal solid waste management segregation disposal |
| url | https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/92/e3sconf_icgest2023_02018.pdf |
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