Abstract: In recent years, occupational accidents have been increasing, and it has been suggested that this increase is related to poor or no supervision of personal protective equipment (PPE) use. This study proposes developing a system capable of identifying the use of PPEs using artificial intelligence through a neural network called YOLO. The results obtained from the development of the system suggest that automatic recognition of PPEs using artificial intelligence is possible with high precision. The recognition of gloves is the only critical object that can give false positives, but it can be addressed with a redundant system that performs two or more consecutive recognitions. This study also involved the preparation of a custom dataset for training the YOLO neural network. The dataset includes images of workers wearing different types of PPEs, such as helmets, gloves, and safety shoes. The system was trained using this dataset and achieved a precision of 98.13% and a recall of 86.78%. The high precision and recall values indicate that the system can accurately identify the use of PPEs in real-world scenarios, which can help prevent occupational accidents and ensure worker safety.

Josue Airton Lopez Cabrejos and Avid Roman-Gonzalez, “Artificial Intelligence System for Detecting the Use of Personal Protective Equipment” International Journal of Advanced Computer Science and Applications(IJACSA), 14(5), 2023. http://dx.doi.org/10.14569/IJACSA.2023.0140561

@article{Cabrejos2023,
title = {Artificial Intelligence System for Detecting the Use of Personal Protective Equipment},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.0140561},
url = {http://dx.doi.org/10.14569/IJACSA.2023.0140561},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {5},
author = {Josue Airton Lopez Cabrejos and Avid Roman-Gonzalez}
}