| Abstrakt: |
Waste segregation is an important strategy in Municipal Waste Management (MWM) systems that involves the deliberate separation of various forms of rubbish at their source. This approach has a substantial impact on resource management as well as urban sustainability. Municipalities can profit from categorizing waste as biodegradable or non-recyclable. Segregation of waste minimizes landfill load and hazardous material release, resulting in healthier soil, water, and air. It also contributes to the circular economy concept by allowing for the recovery of valuable resources from recyclable waste, lowering raw material demand, and lowering energy usage. The system uses YOLOv7, a cutting-edge object identification model, to reliably identify and categorize various waste types in real time. The program can identify various trash categories, such as plastic, paper, glass, and organic garbage, after thorough training on a large dataset, allowing for exact sorting. In waste collection zones, IoT devices such as sensors and cameras are strategically placed to take photographs. The Internet of Things components continuously monitor environmental conditions and possible threats, allowing for prompt intervention to avert overflows or contamination. This comprehensive solution combines YOLOv7's powerful object recognition capabilities with IoT's data-driven insights to create an intelligent trash management framework that improves sorting accuracy and encourages environmentally friendly waste disposal practices. Finally, the incorporation of YOLOv7 and IoT in municipal trash segregation is a possible answer to the challenges of modern garbage management. [ABSTRACT FROM AUTHOR] |
