###### Abstract  
The electric power industry poses significant risks to workers with a wide range of hazards such as electrocution, electric shock, burns, and falls. Regardless of the types and characteristics of these hazards, electric power companies should protect their workers and provide a safe and healthy working environment, but it is difficult to identify the potential health and safety risks present in their workplace and take appropriate action to keep their workers free from harm. Therefore, this paper proposes a novel safety autonomous platform (SAP) for data-driven risk management in the electric power industry. It can automatically and precisely provide a safe and healthy working environment with the cooperation of safety mobility gateways (SMGs) according to the safety rule and risk index data created by the risk level of a current task, a worker profile, and the output of an on-site artificial intelligence (AI) engine in the SMGs. We practically implemented the proposed SAP architecture using the Hadoop ecosystem and verified its feasibility through a performance evaluation of the on-site AI engine and real-time operation of risk assessment and alarm notification for data-driven risk management. e +
Footnote †: journal: Applied  
article  
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Footnote †: journal: Applied  
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ISO45001 is an international standard for industrial health and safety management systems, which includes requirements to reduce the risk at workplaces worldwide, enhance worker safety, create safe working conditions, and reduce employee burden [6]. Based on ISO45001, the Korean legislature enacted the Serious Accident Punishment Act (SAPA), which imposes criminal liability on individuals and entities responsible for serious accidents, including industrial accidents that cause death, serious injury, or occupational illness [7]. Also, the SAPA requires enterprises to establish relevant standards and measures to ensure a certain level of operational safety, including the safety and health of all employees. Thus, electric power companies should comply with this SAPA, protect their workers, and ensure a safe and healthy working environment, regardless of the types and characteristics of hazards mentioned above. As occupational safety and health has received considerable attention from electric power companies, previous studies have identified various hazard scenarios and key causes of accidents such as direct contact with live power sources, the improper wearing of protective equipment, improperly installed or damaged equipment, unsafe operation and the unconsciousness of personnel, unsafe equipment or installation, undesirable environments, and improper work practices [8; 9; 10; 11]. In addition, safety interventions such as knowledge-driven recognition methodology, improved bode accident causation model, workplace wellness programs, etc. have been implemented to mitigate these hazards [12; 13]. However, research on data-driven platforms to automatically and precisely provide a safe and healthy working environment in the electric power industry is still in its early stages because it is difficult to identify the potential health and safety risks present in different workplaces and take appropriate action to keep workers free from harm. Furthermore, there are around 293 types of risk checklists for the electric power industry in Korea [14]. To overcome these challenges in the electric power industry, we propose a safety autonomous platform (SAP) with the cooperation of safety mobility gateways (SMGs) for data-driven risk management using the safety rule and risk index data created by the risk level of a current task, a worker profile, and the output of an on-site artificial intelligence (AI) engine in the SMGs. The rest of this paper is organized as follows. Section 2 describes the configuration and operation of the proposed SAP for data-driven risk management in detail. Section 3 explains an on-site AI engine with multimodal ensemble models and a risk index estimation method with a safety rule.