Development and research of software for monitoring the use of personal protective equipment at the enterprise

I.N. Tomilov, E.E. Istratova, M.A. Kireenko

Abstract


The article presents the results of the development and research of software for monitoring the use of personal protective equipment at the enterprise. This solution was designed based on the use of neural networks and computer vision technology. To determine the effectiveness of the designed model, training and testing were carried out on a data set that included 1644 images of various types of personal protective equipment (helmets, gloves, vests and pants), divided into 4 classes. The model was trained over 152 epochs. The results of the study demonstrated the high efficiency of the proposed integrated approach in solving the problems of automating the process of monitoring the use of personal protective equipment at the enterprise. The developed software allows monitoring the use of personal protective equipment with an average accuracy of more than 94% in real time for moving and static objects and has the ability to recognize a wide range of personal protective equipment, which include: helmets, protective vests, masks, gloves, special clothing. Thus, the finished software product can be used in various industries, including: construction, mechanical engineering, chemical industry, metallurgy, energy.


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References


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