Computer vision aids in detecting personal protective equipment (PPE) by analyzing images or video streams to ensure workers comply with safety protocols. Models trained on datasets of PPE types, such as helmets, gloves, and vests, can identify whether workers are wearing the required gear.
Deep learning models like YOLO or Faster R-CNN are used for real-time detection, alerting supervisors if non-compliance is detected. These systems are particularly effective in industries like construction and manufacturing, where safety risks are high.
By automating PPE compliance monitoring, computer vision enhances workplace safety and reduces the risk of accidents.