AI Intelligent Recognition Early Warning System for Steel Mills - Jiang, Yuan; Chen, Luyu; Li, Zhe; Xu, Xinchen; Su, Yuzhen; Pei, Xun (International Journal of Computer Science and Information Technology, 2025)
The production environment of steel mills is complex, and the equipment is not allowed to stop. The traditional manual monitoring is inefficient, and it is impossible to always monitor data and equipment, which has great security risks. In this paper, an ai intelligent identification and early warning system for steel mills is designed, which integrates two subsystems: safety production early warning and equipment healthy operation early warning, and adopts computer vision (YOLOv5) and time series data analysis (LSTM, self-encoder) technologies respectively to realize workers’ behavior monitoring and equipment fault prediction. Through real-time alarm and data visualization, the system can significantly improve the safety and operational efficiency of steel mills.