Waste Segregation Using YOLOv10 for Sustainable Waste Management

Inadequate waste separation and its recycling can lead to serious environmental and human health damage. Unorganized landfilling of trash reduces the precious area and prevents reprocessing. The organic waste undergoes decomposition without oxygen to produce dangerous greenhouse gases, like methane. Other recyclable materials, such as plastic, decompose in hundreds of years and contaminate areas on land and water bodies. Inadequate waste disposal will further contribute to unhygienic environments that attract pests, endangering public health. On the other hand, not segregating and recycling wastes tons of valuable resources and has irreconcilable impacts on environmental degradation. The proposed research outlines an end-to-end framework for waste management and recycle optimization using YOLO v10(You Only Look Once), one of the cutting-edge object detection algorithms. This research focuses on building a dataset specifically related to the classification of waste and the identification of recyclables. It is then trained on the dataset, and this trained YOLO v10 model is used to allow for the accurate and efficient detection of several waste materials and recyclable items. The proposed methodology is bound to revolutionize waste management practices by automating sorting and recycling-two very major ways to promote sustainability and environmental conservation.