| Autor: |
William, P., Patil, Jaikumar M., Panda, Sunita, Venugopal, Anita, Vidyullatha, Pellakuri, Kumar, Nellore Manoj, Jandwani, Aman |
| Zdroj: |
International Journal of Information Technology; December 2024, Vol. 16 Issue: 8 p5033-5040, 8p |
| Abstrakt: |
Nation’s rapid urbanization growth and economic development, waste generation has significantly increased. An important environmental concern on a global scale is waste management. In a majority of the world’s nations, including India’s metropolitan centers, organic waste management is a major problem. Therefore, it is necessary to create a productive system that will either eliminate or significantly decrease this issue. It will assist us in effectively maintaining a hygienic environment, and natural atmosphere. The implementation of smart cities requires an effective garbage collection system. In the given paper, we propose a smart waste collection and management (SWCM) system centered on the Internet of Things (IoT) architecture. A deep learning (DL) approach for classifying waste is being used. The proposed framework includes the use of smart bins for the collection of garbage, the categorization of that waste into several groups, and the management of smart waste. For this study, data from smart garbage cans were gathered. The data was normalized during preprocessing. The efficacy of the proposed system is assessed and compared with conventional as well as existing recent studies based on performance metrics such as classification accuracy (%) and power consumption (%). The results of the study reveal that the proposed approach is impactful in the smart collection and management of waste. |
| Databáze: |
Supplemental Index |
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