@article{ART002944869},
author={Kim Hyun-A and LEE KYU TAE},
title={Automatic safety helmet detection with Machine Learning},
journal={Journal of Software Assessment and Valuation},
issn={2092-8114},
year={2023},
volume={19},
number={1},
pages={53-59},
doi={10.29056/jsav.2023.3.07}
TY - JOUR
AU - Kim Hyun-A
AU - LEE KYU TAE
TI - Automatic safety helmet detection with Machine Learning
JO - Journal of Software Assessment and Valuation
PY - 2023
VL - 19
IS - 1
PB - Korea Software Assessment and Valuation Society
SP - 53
EP - 59
SN - 2092-8114
AB - More than 50% of safety accidents at work sites, by the statistics of accident situations in the industry, have been caused by falling off and falling down. Accordingly, it is required to wear a safety helmet to prevent head injury. Currently, a system in which work supervisors patrol the site and check whether the helmet is worn and the safety situation is being implemented. However, it is difficult to continuously supervise work. In order to prevent safety accidents, it is necessary to establish an automatic management and supervision system by system for wearing personal protective equipment at the work site. Also a system is required to generate warning signals. In this study, a safety helmet-wearing detection system was developed by porting an artificial intelligence model to Raspberry Pi. A model was constructed to detect whether or not a helmet was worn using object detection computer vision technology. The system generates a warning sound when not wearing a helmet is detected. The system was mounted on a mobile body and analyzed images. The detection accuracy was achieved 87%, and through the process of converting to TensorFlow lite file, fps performance improved by 20% compared to the existing TensorFlow model.
KW - safety accident;safety helmet;object detection;model train;tensorflow
DO - 10.29056/jsav.2023.3.07
ER -
Kim Hyun-A and LEE KYU TAE. (2023). Automatic safety helmet detection with Machine Learning. Journal of Software Assessment and Valuation, 19(1), 53-59.
Kim Hyun-A and LEE KYU TAE. 2023, "Automatic safety helmet detection with Machine Learning", Journal of Software Assessment and Valuation, vol.19, no.1 pp.53-59. Available from: doi:10.29056/jsav.2023.3.07
Kim Hyun-A, LEE KYU TAE "Automatic safety helmet detection with Machine Learning" Journal of Software Assessment and Valuation 19.1 pp.53-59 (2023) : 53.
Kim Hyun-A, LEE KYU TAE. Automatic safety helmet detection with Machine Learning. 2023; 19(1), 53-59. Available from: doi:10.29056/jsav.2023.3.07
Kim Hyun-A and LEE KYU TAE. "Automatic safety helmet detection with Machine Learning" Journal of Software Assessment and Valuation 19, no.1 (2023) : 53-59.doi: 10.29056/jsav.2023.3.07
Kim Hyun-A; LEE KYU TAE. Automatic safety helmet detection with Machine Learning. Journal of Software Assessment and Valuation, 19(1), 53-59. doi: 10.29056/jsav.2023.3.07
Kim Hyun-A; LEE KYU TAE. Automatic safety helmet detection with Machine Learning. Journal of Software Assessment and Valuation. 2023; 19(1) 53-59. doi: 10.29056/jsav.2023.3.07
Kim Hyun-A, LEE KYU TAE. Automatic safety helmet detection with Machine Learning. 2023; 19(1), 53-59. Available from: doi:10.29056/jsav.2023.3.07
Kim Hyun-A and LEE KYU TAE. "Automatic safety helmet detection with Machine Learning" Journal of Software Assessment and Valuation 19, no.1 (2023) : 53-59.doi: 10.29056/jsav.2023.3.07
