Waste management is recognized as a crucial issue in modern civilization, requiring substantial effort and resources while significantly impacting various societal aspects. In sustainable cities striving to eliminate carbon emissions, implementing effective waste management strategies is prioritized. Tackling the three interconnected challenges in trash management, including preventing overflow, tracking bin locations, and designing efficient garbage collection routes, is complex. Current methods often provide incomplete solutions for all three aspects simultaneously. To overcome these difficulties, a smart waste management framework was proposed for environmentally friendly cities, combining the Internet of Things (IoT), long-range (LoRa) technology, and Deep Learning techniques. The proposed system utilized ultrasonic sensors equipped with a LoRa connection to facilitate the real-time monitoring of bin status. Prompt intervention to prevent overflow scenarios was facilitated. Integrating the Floyd-Warshall algorithm enhanced the garbage collection route efficiency by considering the bin fill levels and their exact locations. Deployment was made affordable and straightforward using inexpensive IoT components, including LoRa modules, facilitating smooth data transfer. In addition, incorporating RecycleCnn, implemented using Python with TensorFlow and Keras frameworks, enhanced the proposed framework by enabling automatic garbage classification with a 98% accuracy rate. This classification system facilitated the categorization of garbage into specific groups, improved recycling initiatives, and advocated for sustainable waste management methods. The proposed system used Arduino UNO microcontrollers, ultrasonic sensors, and LoRaWAN technologies to provide a precise and effective method for assessing garbage levels and controlling waste distribution. This holistic approach to intelligent waste management seeks to provide cleaner, pollution-free urban environments by addressing problems arising from ineffective garbage collection methods. The proposed framework addressed trash management and recycling challenges while laying the foundation for sustainable development projects in smart towns like Khandagiri and Pokhariput. Also, it provided a comprehensive approach to garbage collection, categorization, and management.
Laha et al. (Tue,) studied this question.