Labor Safety Analysis Using Object Recognition and Deep Learning

Occupational safety is a major concern in any industry or workplace, and the use of advanced technologies such as object recognition and deep learning can greatly enhance safety measures. This paper proposes a labor safety analysis system that utilizes object recognition and deep learning algorithms to detect potential hazards and ensure safe working conditions. The proposed system can recognize various types of safety gear and analyze their positions and movements to detect potential safety in real time. The system can also provide alerts and warnings to workers and supervisors in case of the absence of safety gear. Experimental results demonstrate the effectiveness and efficiency of the proposed work. This can significantly improve the safety and productivity of the workplace.