A Dual-Model Approach to Industrial Safety: Computer Vision for PPE Compliance and Hazard-Zone Monitoring in Steel Production

Abstract Experimental evaluation demonstrates strong performance, achieving an F1 score of 0.92 for worker detection and 0.93 for personal protective equipment (PPE) classification. The integrated hazard-zone monitoring module further enables spatial safety enforcement, achieving a frame-level detection accuracy of 92% for restricted-area violations. The system supports real-time monitoring and processes video streams at approximately 35 ms per frame on a standard GPU. Preliminary deployment observations in an operational steel facility suggest that the system can assist safety personnel by improving visibility of PPE compliance and restricted-area monitoring. These results demonstrate the technical feasibility of the proposed modular framework as a scalable approach for automated industrial safety monitoring.