AI-Enhanced Detection of Hazardous Materials in Metal Scrap for Safer Industrial Operations

Well-regulated safety is indispensable in scrap-based liquid alloy manufacturing specifically in settings that employ induction furnaces within, in the realm of the metal based scrap industry unit that drives eco-efficient engineering by converting waste into valuable resources strengthening the repurposing of scrap into steel bars reduces dependence on naturally sourced materials enhances resource-efficient energy use and mitigates environmental disruption however the presence of hazardous items such as gas cylinders and pressurized canisters poses significant risks in high-temperature recycling operations To address these challenges we present an automated approach to hazardous substance detection using advanced computer vision techniques our enhanced modern system leverages a custom dataset developed using client- provided and web-sourced images of metal scrap annotated with smart polygon shapes to capture object contours accurately ,where single-shot detector model which is YOLO(You Look Only Once) versions such as yolov9 ,yolov8 and its variants were used and evaluated through extensive data preprocessing and augmentation strategies , yolov9 was selected for deployment due to its superior performance the model achieved a mAP(mean average precision) of 0.86 on test data enabling precise detection and classification of hazardous materials within industrial settings Our solution serves as a safeguard for operational safety, preventing catastrophic events such as chemical reactions, explosions, and toxic emissions that could endanger human lives and disrupt production, as safety becomes important when scraps are melted, as during this process presence of closed substances can cause tremendous effects to environment and workers. Deployed via Streamlit(open- source Python framework), the model provides real-time monitoring of live video feeds, enhancing safety measures and operational efficiency in scrap-based liquid steel production. This automated system not only mitigates risks but also ensures compliance with safety regulations, ultimately improving the integrity and sustainability of industrial processes.