Factory Worker Safety Mask Monitoring System Based on Deep Learning and AI Edge Computing
Donghui Fang, Liguo Tian, Meng Li, Yuesong Wang, Jinqi Liu, Xiang Chen · 2022
When factory workers work on a daily basis, safety accidents may occur due to goggles and protective masks not being worn or not being worn in a standardized manner. Such accidents put workers’ lives and health at risk, damage factory equipment, and can cause serious fires and injuries. The system uses Artificial Intelligence (AI) and AI edge computing to monitor workers’ protective equipment, using deep learning to train a suitable model, which is remotely transmitted to the AI edge computing module Jetson Nano via Secure Shell (SSH) protocol, and finally the AI edge computing module determines the workers’ protective equipment wearing situation. The AI edge computing module provides some practical value for the prevention of factory safety accidents, and also provides a reliable basis for the establishment of smart factories.