International Journal of Science, Engineering and TechnologyAuthors: shivraahul B, vishal Sanjay R, Dr. Saravanakumar R
Abstract: Human fatigue and drowsiness can reduce attention and task performance, motivating the development of real-time monitoring systems that combine behavioral and physiological indicators. This paper presents a low-cost prototype that combines galvanic skin response (GSR) sensing with vision-based facial analysis. An R-1085 GSR sensor is interfaced to an ESP32 for analog signal acquisition and USB serial transmission. A conventional laptop camera provides facial images, while Python, OpenCV and MediaPipe facial landmarks are used to estimate eye aspect ratio (EAR) and identify prolonged eye closure. LabVIEW 2022 is proposed as the supervisory monitoring layer for visualization and alert presentation, with a buzzer available for warning output. Initial GSR experiments using 35 finger-contact samples produced values from 2242 to 2270 (mean 2262.4; standard deviation 4.75),whereas 37 no-contact samples ranged from 2366 to 2490 (mean 2400.38; standard deviation 23.81). The camera prototype produced EAR values of 0.39 for an open-eye frame and 0.19 for a closed-eye frame. These preliminary results demonstrate operation of the individual sensing components. The prototype is intended for research and educational evaluation; the measured thresholds are not clinically validated fatigue criteria.
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