Design of smart waste bin and prediction algorithm for waste management in household area
Maintaining current municipal solid waste management (MSWM) for the next ten years would not be efficient anymore as it has brought many environmental issues such as air pollution. This project has proposed Artificial Neural Network (ANN) based prediction algorithm that can forecast Solid Waste Gene...
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| Format: | Article |
| Language: | English English |
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Institute of Advanced Engineering and Science
2018
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| Online Access: | http://irep.iium.edu.my/66227/ http://irep.iium.edu.my/66227/1/66227_Design%20of%20smart%20waste%20bin.pdf http://irep.iium.edu.my/66227/2/66227_Design%20of%20smart%20waste%20bin_SCOPUS.pdf |
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| author | Yusoff, Siti Hajar Abdullah Din, Ummi Nur Kamilah Mansor, Hasmah Midi, Nur Shahida Zaini, Syasya Azra |
| author_facet | Yusoff, Siti Hajar Abdullah Din, Ummi Nur Kamilah Mansor, Hasmah Midi, Nur Shahida Zaini, Syasya Azra |
| author_sort | Yusoff, Siti Hajar |
| building | IIUM Repository |
| collection | Online Access |
| description | Maintaining current municipal solid waste management (MSWM) for the next ten years would not be efficient anymore as it has brought many environmental issues such as air pollution. This project has proposed Artificial Neural Network (ANN) based prediction algorithm that can forecast Solid Waste Generation (SWG) based on household size factor. Kulliyyah of Engineering (KOE) in International Islamic University Malaysia (IIUM) has been chosen as the sample size for household size factor. A smart waste bin has been developed that can measure the weight, detect the emptiness level of the waste bin, stores information and have direct communication between waste bin and collector crews. This study uses the information obtained from the smart waste bin for the waste weight while the sample size of KOE has been obtained through KOE’s department. All data will be normalized in the pre-processing stage before proceeding to the prediction using Visual Gene Developer. This project evaluated the performance using R2 value. Two hidden layers with five and ten nodes were used respectively. The result portrayed that the average rate of increment of waste weight is 2.05 percent from week one until week twenty. The limitation to this study is that the amount of smart waste bin should be replicated more so that all data for waste weight is directly collected from the smart waste bin. |
| first_indexed | 2025-11-14T17:10:36Z |
| format | Article |
| id | iium-66227 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-14T17:10:36Z |
| publishDate | 2018 |
| publisher | Institute of Advanced Engineering and Science |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | iium-662272018-09-12T02:10:31Z http://irep.iium.edu.my/66227/ Design of smart waste bin and prediction algorithm for waste management in household area Yusoff, Siti Hajar Abdullah Din, Ummi Nur Kamilah Mansor, Hasmah Midi, Nur Shahida Zaini, Syasya Azra TK4001 Applications of electric power Maintaining current municipal solid waste management (MSWM) for the next ten years would not be efficient anymore as it has brought many environmental issues such as air pollution. This project has proposed Artificial Neural Network (ANN) based prediction algorithm that can forecast Solid Waste Generation (SWG) based on household size factor. Kulliyyah of Engineering (KOE) in International Islamic University Malaysia (IIUM) has been chosen as the sample size for household size factor. A smart waste bin has been developed that can measure the weight, detect the emptiness level of the waste bin, stores information and have direct communication between waste bin and collector crews. This study uses the information obtained from the smart waste bin for the waste weight while the sample size of KOE has been obtained through KOE’s department. All data will be normalized in the pre-processing stage before proceeding to the prediction using Visual Gene Developer. This project evaluated the performance using R2 value. Two hidden layers with five and ten nodes were used respectively. The result portrayed that the average rate of increment of waste weight is 2.05 percent from week one until week twenty. The limitation to this study is that the amount of smart waste bin should be replicated more so that all data for waste weight is directly collected from the smart waste bin. Institute of Advanced Engineering and Science 2018-11-02 Article PeerReviewed application/pdf en http://irep.iium.edu.my/66227/1/66227_Design%20of%20smart%20waste%20bin.pdf application/pdf en http://irep.iium.edu.my/66227/2/66227_Design%20of%20smart%20waste%20bin_SCOPUS.pdf Yusoff, Siti Hajar and Abdullah Din, Ummi Nur Kamilah and Mansor, Hasmah and Midi, Nur Shahida and Zaini, Syasya Azra (2018) Design of smart waste bin and prediction algorithm for waste management in household area. Indonesian Journal of Electrical Engineering and Computer Science, 12 (2). pp. 748-758. ISSN 2502-4752 http://iaescore.com/journals/index.php/IJEECS/article/view/14548/9405 10.11591/ijeecs.v12.i2.pp748-758 |
| spellingShingle | TK4001 Applications of electric power Yusoff, Siti Hajar Abdullah Din, Ummi Nur Kamilah Mansor, Hasmah Midi, Nur Shahida Zaini, Syasya Azra Design of smart waste bin and prediction algorithm for waste management in household area |
| title | Design of smart waste bin and prediction algorithm for waste management in household area |
| title_full | Design of smart waste bin and prediction algorithm for waste management in household area |
| title_fullStr | Design of smart waste bin and prediction algorithm for waste management in household area |
| title_full_unstemmed | Design of smart waste bin and prediction algorithm for waste management in household area |
| title_short | Design of smart waste bin and prediction algorithm for waste management in household area |
| title_sort | design of smart waste bin and prediction algorithm for waste management in household area |
| topic | TK4001 Applications of electric power |
| url | http://irep.iium.edu.my/66227/ http://irep.iium.edu.my/66227/ http://irep.iium.edu.my/66227/ http://irep.iium.edu.my/66227/1/66227_Design%20of%20smart%20waste%20bin.pdf http://irep.iium.edu.my/66227/2/66227_Design%20of%20smart%20waste%20bin_SCOPUS.pdf |