Recognition System for Safety Helmets and Reflective Clothing in Power Transmission Engineering Construction Based on Machine Vision

The safety production management of power transmission engineering is an important guarantee for improving the infrastructure work of the power grid, and safety helmets and reflective clothing play a crucial role in protecting personnel's heads and bodies in the construction and production environment. The supervision of wearing safety helmets and reflective clothing is an indispensable link in high-risk working environments. For this purpose, this article designs a multi node transmission engineering helmet reflective vest recognition system based on machine vision. The system includes sensor nodes, center nodes, computing nodes, and a front-end panel program responsible for displaying information. The four programs communicate through the MQTT protocol and a built MQTT Broker program. The sensor node transmits the data of the connected camera to the front-end program through the MQTT protocol. At the same time, under the scheduling of the central node, the camera data is sent to the computing node for target recognition calculation using the YOLO algorithm to identify the wearing status of the personnel's safety helmets and reflective clothing in the image. The recognition result is then sent to the front-end program, which displays the camera image together with the recognition result. The research results of the paper not only accurately identify the wearing of safety helmets and reflective clothing by personnel during power construction, but also provide an effective solution for the design of intelligent monitoring systems.