A Vision based Deep-Learning Approach for Solid Waste Management towards Sustainable Environment in India

One of the major challenges in a developing country like India is the solid waste management due to rapid urbanization, inadequate infrastructure, poor segregation, and low public awareness. On the other hand, the generation of solid waste is increasing rapidly. Henceforth, effective solid waste management (SWM) is very important for a sustainable environment and a healthy society. This research work proposes a modified deep learning-based YOLO model for solid waste classification that can assist the separation-based waste identification and management. The model includes an additional convolutional layer to improve feature extraction and scale sensitivity. It predicts the center coordinates, width, height, and confidence score for each bounding box with adequate accuracy. Proper waste classification makes waste collection, waste transport, and waste treatment more effective and efficient. The results show the effectiveness of the proposed methodology.