Safety Hazards Detections in Electrical Industry: A Systematic Literature Review

The electrical sector drives economic growth and poses significant occupational health and safety challenges. The dynamic nature of electrical infrastructure and the expansion of power plants and distribution networks, particularly in Indonesia, heightens the risk of electricity-related workplace accidents. However, Indonesia's limited research focuses on hazard detection within the electrical industry. This study aims to map the factors contributing to hazards and methods to detect hazards in the electrical industry with several contributing factors, particularly human factors, in identifying potential hazards and mitigating accident risks. The search engines utilized in this study included Science Direct, Google Scholar, Taylor & Francis Online, MDPI, and the Institute of Electrical and Electronics Engineers (IEEE). A total of 2,446 articles were initially reviewed, and after thorough screening, 15 articles were selected for further analysis. The results show some factors contributing to safety hazard detection, including human, environmental, organizational, technological, and physical factors. The factors with the most substantial evidence demonstrated a significant level of P< 0.001. Subsequently, some methods were used for the detection of hazards, such as surveys, interviews, machine learning, deep learning, eye tracking, and virtual reality, which are applied in power plants, transmission, and distribution electrical sectors. Future research could focus on IoT for hazard detection, work culture, and enhancing the human-machine interface.