Abstract
Drowsiness in car or truck drivers has been a major cause of road accidents and it is inevitable that we determine the drowsiness of the driver in advance and take preventive actions. Three key physiological factors that act as indicators of drowsiness in a driver are closing of eyes, yawning and heart rate falling between 40 and 60 beats per minute. In this paper, image processing and machine learning based driver sleep detection (DSD) system is proposed. It mainly involves detection of closed eyes, yawning and monitoring of heart rate. The information of DSD system is stored in a cloud platform and can be accessed and utilized anytime for analysis purposes.
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