Citation

Li G, Jiang Y, Wang C. China Saf. Sci. J. 2022; 32: 118-122.

Copyright

(Copyright © 2022, China Occupational Safety and Health Association, Publisher Gai Xue bao)

DOI

10.16265/j.cnki.issn1003-3033.2022.S2.0176

PMID

unavailable

Abstract

In order to monitor and warn the occupational hazard factors at the production site in real time and ensure the occupational health and safety of the employees, a hydropower station took occupational health and safety hazard factors in underground chambers and workshops as research objects. These factors included toxic and harmful gas, noise, and electromagnetic radiation. In addition, the station used big data, cloud computing, artificial intelligence, Internet, Internet of things, and other technologies to design and develop a software and hardware system. The system could prevent and control occupational hazard factors in real time. The station also built an intelligent occupational health monitoring and warning system. The results show that the construction of occupational health information infrastructure, application system, and network security configuration in the hydropower industry are coordinated by the warning system. Real-time perception and monitoring devices for occupational hazard factors in underground caves are comprehensively deployed according to the prevention and control standard of occupational hazard factors. In addition, a risk warning algorithm model for occupational hazard factors exceeding the standard is constructed. On the one hand, the model can dynamically monitor occupational hazard factors, such as toxic and harmful gas, noise, and electromagnetic radiation in real time. On the other hand, it can ensure comprehensive analysis and early warning. The occupational health monitoring and warning system is established and implemented. As a result, the system eliminates the defects of traditional manual periodic detection and realizes the comprehensive and long-term control and prevention of occupational hazard factors. © 2022 China Safety Science Journal

Language: zh