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In contemporary urban landscape, the efficient management of waste poses a critical challenge necessitating innovative solutions. This study delves into the realm of IoT-enabled smart waste management, elucidating the integration of sensor technologies and implementation strategies for enhanced operational efficacy. This research work presents a comprehensive investigation into IoT-enabled smart waste management systems, focusing on the integration of sensor technologies and implementation strategies. The study addresses the growing need for efficient waste management solutions in urban environments by proposing a novel algorithm, IoTBinCap, which optimizes waste collection schedules based on real-time data from IoT sensors installed in garbage bins. Through simulation analysis, the performance of IoTBinCap is compared with existing algorithms using appropriate metrics such as collection efficiency, bin utilization, and route optimization. The results demonstrate the effectiveness of IoTBinCap in improving resource utilization and minimizing waste overflow instances compared to traditional algorithms. Additionally, the research explores various sensor technologies and implementation strategies, highlighting their roles in enhancing waste monitoring, sorting, and collection processes. The findings contribute to the advancement of smart waste management systems, offering insights for policymakers, urban planners, and waste management authorities.
Sankar et al. (Wed,) studied this question.
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