| spelling |
oapen-20.500.12657-890662024-04-03T02:23:06Z Chapter iSafe Welding System: Computer Vision-Based Monitoring System for Safe Welding Work Abbas, Muhammad Sibtain Zaidi, Syed Farhan Alam Hussain, Rahat Yang, Jaehun Lee, Doyeop Park, Chansik Safety monitoring scene classification welding work fire prevention construction safety OSHA rules compliance thema EDItEUR::U Computing and Information Technology The construction industry faces significant challenges, including a high prevalence of occupational incidents, often involving fires, explosions, and burn-related accidents due to worker non-compliance with safety protocols. Adherence to safety guidelines and proper utilization of safety equipment are critical to preventing such incidents and safeguarding workers in hazardous work environments. Consequently, a monitoring system tailored for construction safety during welding operations becomes imperative to mitigate the risk of fire accidents. This paper conducts a brief analysis of OSHA rules pertaining to welding work and introduces the iSafe Welding system, an advanced real-time safety monitoring and compliance enforcement solution designed specifically for construction site welding operations. Harnessing the real-time object detection algorithm YOLOv7 in conjunction with rule-based scene classification, the system excels in identifying potential safety violations. Rigorous evaluation, encompassing precision, recall, mean Average Precision (mAP), accuracy, and the F1-Score, sheds light on its strengths and areas for improvement. The system showcases robust performance in rule-based scene classification, achieving high accuracy, precision, and recall rates. Notably, the iSafe Welding system demonstrates a formidable potential for enhancing construction site safety and regulatory compliance. Ongoing enhancements, including dataset expansion and model refinement, underscore its commitment to real-world deployment and its strength in ensuring worker safety 2024-04-02T15:45:27Z 2024-04-02T15:45:27Z 2023 chapter ONIX_20240402_9791221502893_35 2704-5846 9791221502893 https://library.oapen.org/handle/20.500.12657/89066 eng Proceedings e report application/pdf n/a 9791221502893_66.pdf https://books.fupress.com/doi/capitoli/979-12-215-0289-3_66 Firenze University Press 10.36253/979-12-215-0289-3.66 10.36253/979-12-215-0289-3.66 bf65d21a-78e5-4ba2-983a-dbfa90962870 9791221502893 137 7 Florence open access
|
| description |
The construction industry faces significant challenges, including a high prevalence of occupational incidents, often involving fires, explosions, and burn-related accidents due to worker non-compliance with safety protocols. Adherence to safety guidelines and proper utilization of safety equipment are critical to preventing such incidents and safeguarding workers in hazardous work environments. Consequently, a monitoring system tailored for construction safety during welding operations becomes imperative to mitigate the risk of fire accidents. This paper conducts a brief analysis of OSHA rules pertaining to welding work and introduces the iSafe Welding system, an advanced real-time safety monitoring and compliance enforcement solution designed specifically for construction site welding operations. Harnessing the real-time object detection algorithm YOLOv7 in conjunction with rule-based scene classification, the system excels in identifying potential safety violations. Rigorous evaluation, encompassing precision, recall, mean Average Precision (mAP), accuracy, and the F1-Score, sheds light on its strengths and areas for improvement. The system showcases robust performance in rule-based scene classification, achieving high accuracy, precision, and recall rates. Notably, the iSafe Welding system demonstrates a formidable potential for enhancing construction site safety and regulatory compliance. Ongoing enhancements, including dataset expansion and model refinement, underscore its commitment to real-world deployment and its strength in ensuring worker safety
|
