Wearable and IoT-Integrated Solutions for Electrical Hazard Prevention in Industrial Environments

Md Ferdous Ahmed (), Md Rifat Al Amin Khan () and Md Nazmul Islam ()

Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023, 2025, vol. 8, issue 1, 136-149

Abstract: Electrical hazards remain one of the leading causes of workplace injuries and fatalities in industrial environments, despite advancements in safety protocols. Traditional methods, such as manual lockout/tagout (LOTO) procedures, often fail due to human error and lack of real-time monitoring. This paper proposes an innovative framework that integrates wearable technology with Internet of Things (IoT) systems to proactively mitigate electrical hazards. The wearable devices, equipped with voltage detection sensors, provide real-time alerts to workers approaching energized equipment, while IoT-enabled environmental sensors and cloud-based analytics predict potential hazard zones. A six-month field trial conducted across three manufacturing sites demonstrated significant improvements in worker safety, including a 73% reduction in near-miss incidents and a 75% decrease in emergency response times. The proposed system also enhanced compliance with safety protocols through automated monitoring and reporting. This study highlights the scalability, operational benefits, and challenges of implementing wearable IoT solutions in industrial settings, paving the way for smarter and safer workplaces. Future work will focus on integrating artificial intelligence for anomaly detection and augmented reality for immersive training programs.

Keywords: Electrical hazard prevention; IoT wearables; industrial safety; predictive analytics; real-time monitoring (search for similar items in EconPapers)
Date: 2025
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