• O. Krainiuk Kharkiv National Automobile and Highway University
  • Yu. Buts Kharkiv National Automobile and Highway University
  • V. Barbashyn O.M. Beketov National University of Urban Economy in Kharkiv
  • M. Yatsiuk O.M. Beketov National University of Urban Economy in Kharkiv



occupational safety, industrial injuries, machine learning, neural networks, sensors


Artificial intelligence introduces innovations in the field of monitoring, diagnostics, and management in the production environment, allowing for reducing the risks of industrial accidents, improving the quality of work, and contributing to the increase of production efficiency. The article considers the main aspects of the application of artificial intelligence for security at enterprises, explores various methods and technologies, and analyses examples of successful implementations in various industries. We also discuss the challenges and prospects related to this topic and closely examine the impact of artificial intelligence on the future of industrial safety.

The article aims to study the possibilities of artificial intelligence for solving labour safety problems. The task is to evaluate the potential areas of implementation and algorithms of neural networks, which could reduce the number of dangerous factors associated with human activity at work and increase the level of occupational safety. With the use of AI, numerous innovative solutions can be created to improve control, predict potential hazards, and reduce risks to workers and equipment. Currently, neural networks are successfully used in the fields of production and labour protection to ensure visual control of compliance with safety measures. An indisputable advantage is the sustainability of monitoring and the exclusion of the human factor from this process. Artificial intelligence allows us to warn of situations related to injuries and non-compliance with safety rules, as well as track potentially dangerous events in any area of production.

Machine vision, a crucial component of artificial intelligence, enhances workplace safety through continuous monitoring, anomaly detection, personnel identification, equipment evaluation, visual training, and video analysis. It improves safety conditions and mitigates risks effectively. Artificial intelligence and AI-powered voice systems are becoming crucial tools for enhancing workplace safety. They aid in preventing industrial accidents, optimising work processes, and innovating safety control and prediction solutions. AI plays a vital role in visual safety monitoring and eliminates the human factor, ensuring reliability and efficiency.

Author Biographies

O. Krainiuk, Kharkiv National Automobile and Highway University

Candidate of Technical Sciences, Associate Professor

Yu. Buts, Kharkiv National Automobile and Highway University

Doctor of Technical Sciences, Professor

V. Barbashyn, O.M. Beketov National University of Urban Economy in Kharkiv

Candidate of Technical Sciences, Associate Professor

M. Yatsiuk, O.M. Beketov National University of Urban Economy in Kharkiv

Candidate of History, Associate Professor


Krainiuk, O. V., Buts, Yu. V., & Barbashyn, V. V. (2021). SWOT analysis of the implementation of digital technologies to ensure occupational safety. Municipal Economy of Cities, 3(163), 234–238. DOI: 10.33042/2522-1809-2021-3-163-234-238

Krainiuk, O. V., Buts, Yu. V., Barbashyn, V. V., & Didenko, N. V. (2020). Prospects of digitalization in the field of occupational health and safety. Municipal Economy of Cities, 6(159), 130–138. DOI: 10.33042/2522-1809-2020-6-159-130-138

Krainiuk, O. V., Buts, Yu. V., Barbashyn, V. V., Lotsman, P. I., & Kalchenko, D. Yu. (2021). Increasing the reliability for measuring the temperature of the surface of the human body. Municipal Economy of Cities, 4(164), 197–202. DOI: 10.33042/2522-1809-2021-4-164-197-202

Krainiuk, O. V., Buts, Yu. V., Barbashyn, V. V., & Didenko, N. V. (2023). Analysis of the spheres of application of unmanned aircraft apparatus for resolving labor safety issues. Municipal Economy of Cities, 1(175), 182–188. DOI: 10.33042/2522-1809-2023-1-175-182-188

Xiao, Q. (2007). Technology review – Biometrics-Technology, Application, Challenge, and Computational Intelligence Solutions. IEEE Computational Intelligence Magazine, 2(2), 5–25. Retrieved from

Baduge, S. K., Thilakarathna, S., Perera, J. S., Arashpour, M., Sharafi, P., Teodosio, B., Shringi, A., & Mendis, P. (2022). Artificial intelligence and smart vision for building and construction 4.0: Machine and deep learning methods and applications. Automation in Construction, 141, Article 104440. DOI: 10.1016/j.autcon.2022.104440

Liu, J., Luo, H., & Liu, H. (2022). Deep learning-based data analytics for safety in construction. Automation in Construction, 140, Article 104302. DOI: 10.1016/j.autcon.2022.104302

Shidik, G. F., Noersasongko, E., Nugraha, A., Andono, P. N., Jumanto, J., & Kusuma, E. J. (2019). A Systematic Review of Intelligence Video Surveillance: Trends, Techniques, Frameworks, and Datasets. IEEE Access, 7, 170457–170473. DOI: 10.1109/ACCESS.2019.2955387

De Stefano, V. (2019). “Negotiating the algorithm”: Automation, artificial intelligence and labor protection. International Labour Office. Retrieved from

Shneiderman, B. (2020). Human-Centered Artificial Intelligence: Reliable, Safe & Trustworthy. International Journal of Human–Computer Interaction, 36(6), 495–504. DOI: 10.1080/10447318.2020.1741118

Chen, M., & Decary, M. (2020). Artificial intelligence in healthcare: An essential guide for health leaders. Healthcare Management Forum, 33(1), 10–18. DOI: 10.1177/0840470419873123

Pishgar, M., Issa, S. F., Sietsema, M., Pratap, P., & Darabi, H. (2021). REDECA: A Novel Framework to Review Artificial Intelligence and Its Applications in Occupational Safety and Health. International Journal of Environmental Research and Public Health, 18(13), Article 6705. DOI: 10.3390/ijerph18136705

Alexander, A., Jiang, A., Ferreira, C., & Zurkiya, D. (2020). An Intelligent Future for Medical Imaging: A Market Outlook on Artificial Intelligence for Medical Imaging Journal of the American College of Radiology, 17(1), 165–170. DOI: 10.1016/j.jacr.2019.07.019

Howard, J. (2019). Artificial intelligence: Implications for the future of work. American Journal of Industrial Medicine, 62(11), 917–926. DOI: 10.1002/ajim.23037



How to Cite

Krainiuk, O., Buts, Y., Barbashyn, V., & Yatsiuk, M. (2023). USE OF ARTIFICIAL INTELLIGENCE FOR WORK SAFETY MANAGEMENT. Municipal Economy of Cities, 6(180), 207–213.

Most read articles by the same author(s)

1 2 > >>