Use of machine learning for prevention of incidents and reduction of occupational risks at the workplace

V.V. Kuleshov; T.G. Aygumov; A.L. Zolkin; A.S. Tychkov; A.S. Bityutskiy

doi:10.1117/12.2680682

27 April 2023 Use of machine learning for prevention of incidents and reduction of occupational risks at the workplace

V.V. Kuleshov, T.G. Aygumov, A.L. Zolkin, A.S. Tychkov, A.S. Bityutskiy

Proceedings Volume 12637, International Conference on Digital Transformation: Informatics, Economics, and Education (DTIEE2023); 126370U (2023) https://doi.org/10.1117/12.2680682
Event: International Conference on Digital Transformation: Informatics, Economics, and Education (DTIEE2023), 2023, Fergana, Uzbekistan

Abstract

This article examines the use of machine learning to prevent incidents and occupational hazards at the workplace. The authors have analyzed existing research in this area and have demonstrated the possibility of use of the machine learning to predict risks and prevent incidents. Specifically, the authors studied the methods of logical regression and classification to analyze data on past incidents. The results of the study showed that the use of machine learning can significantly improve the accuracy of risk prediction and enable more effective incident prevention. The importance of introduction of machine learning is discussed in the context of workplace safety and directions for further research are suggested. Overall, the article is an important addition to the general literature on the use of machine learning in the field of workplace safety and provides an opportunity to better understand the background and improve the accuracy of risk prediction and incident prevention at the workplace. The study is of interest to scientists, practitioners and politicians involved in workplace safety, as well as to those who are involved in the development and implementation of machine learning systems.

Citation Download Citation

V.V. Kuleshov, T.G. Aygumov, A.L. Zolkin, A.S. Tychkov, and A.S. Bityutskiy "Use of machine learning for prevention of incidents and reduction of occupational risks at the workplace", Proc. SPIE 12637, International Conference on Digital Transformation: Informatics, Economics, and Education (DTIEE2023), 126370U (27 April 2023); https://doi.org/10.1117/12.2680682

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