YOLO Network Based Intelligent Municipal Waste Management in Internet of Things
Rajlakshmi Ghatkamble, Bidare Divakarachari Parameshachari, Piyush Kumar Pareek · 2022
It's becoming more worrying that unchecked urban garbage buildup might lead to environmental contamination and potential health risks for city dwellers. People don't use their recycling bins correctly, thus they aren't very effective. IoT and AI advancements have made it possible to replace the outdated trash management infrastructure with one that incorporates smart sensors for real-time monitoring and more efficient waste management. Having a sophisticated, computer-based system to handle garbage is crucial. Hand-picking, or the human separation of garbage into its many components, is an essential part of the waste management process. An intelligent waste material classification system is proposed in this study to streamline the process; it is created utilising a novel methodology based on image processing methods, the diagnosis of photos from waste management. The YOLOv5 public dataset of trash management was used for training, fine-tuning, and testing the suggested technique. The plan also includes the introduction of a smart garbage can's architectural design, which incorporates a microprocessor and many sensors. In order to keep an eye on things, the suggested system uses the Internet of Things and Bluetooth connection. An integral aspect of any effective municipal waste management system is a central monitoring facility that use that data to plan for things like the deployment and maintenance of adaptive equipment, as well as the garbage collection and vehicle routing strategies that bring it all home.