Journal of Dali University ›› 2022, Vol. 7 ›› Issue (12): 37-42.

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Research on Construction Workers' Safety Protection Equipment Wearing Detection Based on YOLOv5s

  

  1. 1.College of EngineeringDali UniversityDaliYunnan 671003China2.School of Information and Electronic EngineeringZhejiang Gongshang UniversityHangzhou 310018China

  • Received:2022-05-05 Online:2022-12-15 Published:2022-12-15

Abstract:

To solve the problem of irregular wearing of safety helmets and masks by construction workers' during operation the YOLOv5s algorithm is used to detect the wearing of safety protection equipment for construction workers to reduce the probability of safety accidents. The YOLOv5s algorithm is combined with the embedded platform Jetson Nano and the TensorRT technology is used to improve the detection frame rate of the YOLOv5s algorithm. The mAP value of the final model is 0.946 and the detection frame rate on the Jetson Nano is 12.83 FPS. The YOLOv5s algorithm is applied to the field of construction site safety assurance which realizes effective monitoring of the wearing of construction workers' helmets and masks and meets the needs of detection speed and portable installation of equipment in practical applications.

Key words: YOLOv5s, target detection, TensorRT, Jetson Nano

CLC Number: