Design and Implementation of A Novel Eye Fatigue Analysis System for Safe Field Workers

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Abstract
This paper proposes a study to analyze worker fatigue and prevent accidents in a smart factory environment. This study utilizes MPE blink (Multi-Person Eyeblink) dataset and InstBlink algorithm to detect the number of eye blinks of workers in real-time and proposes a method to improve the accuracy of the algorithm to measure worker fatigue more accurately. This research plays an important role in improving worker safety and productivity. In manufacturing environments, workers spend long hours working on monitors, often unable to look away from the screen. This can lead to poor eye health and increased fatigue. The system estimates the fatigue level by detecting the worker’s eye blinks before work and displays a warning screen to prohibit physical labor when the number of blinks is detected below 15 per minute. This helps to protect the safety of workers and prevent accidents in the work environment.

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