Abstract
Safety rules and regulations for various groups of organizations are required along with security education, safety supervision and inspection. These measures can improve the level of safety management to a certain extent, and because the employees are disturbed by anxiety and impulsive irrational psychological factors in production and technology and other social activities, their behavior is more difficult to be predicted. This study aims at introducing an enterprise accident and safety early warning system by infusing human factors with respect to physical and the environmental aspects of the behavior, and with respect to safety management needs, and proposes the application of the Internet of things technology to the construction of enterprise early warning system. The accident warning system architecture uses IOT framework as a model, the three-layer structure includes perception layer, transport layer and application layer. The proposed system can help address several issues and can shift the enterprise focus form accident treatment to a more proper and effective accident warning system, and fundamentally help prevent accidents at first.
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Acknowledgements
This research reported herein was supported by the NSFC of China under Grant No. 71571091 and No. 71771112.
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Liu, W., Chen, X., Sun, Q. (2019). Development of Enterprise Accident Early Warning System Based on IOT. In: Arezes, P. (eds) Advances in Safety Management and Human Factors. AHFE 2018. Advances in Intelligent Systems and Computing, vol 791. Springer, Cham. https://doi.org/10.1007/978-3-319-94589-7_14
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DOI: https://doi.org/10.1007/978-3-319-94589-7_14
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