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<p>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&#xa0;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.</p>

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

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月12日

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  • Kyle Toth,
  • Monika Singhal,
  • Dhwanil Chauhan,
  • Jay Polra,
  • Chenn Zhou,
  • Garrett Page,
  • Conrad Fisher

摘要

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.