Workers' Fatigue Status Monitoring System via Wearable Devices

The shortage of manpower in the manufacturing industry is becoming a serious problem, therefore excessive workloads and lack of rest are followed especially in small and medium-sized enterprises. However, workers with high fatigue are the main cause of decreasing efficiency, human errors, and safety accidents. In this study, the architecture of a monitoring system via commercial wearable devices is proposed. In the process, considerations for monitoring design were defined, and the implementation of the proposed system in the experimental environment was designed similarly to machine tool operations. Built AI algorithms show 85% accuracy in fatigue status prediction. Also, it was found that fatigue led to a huge difference during the operation with physical burden and the work performance in the process of programming. The proposed system was designed using commercial smartwatches to have the advantage in its applicability. It will help SMEs realize 'human in the industries' and minimize the adverse effects of workers' fatigue, including human errors, by supporting objective tiredness detection and recommending proper rest at industrial sites.