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doi: 10.33317/ssurj.573
The driver felt sleepy when they don’t take proper rest while driving on long routes. The restless driving careless mistake could be fatal to driver as well as others’ lives. This issue has been increased to such a level that a system required to avoid accidents and save life. The driver alertness detection can play a significant role to avoid such hazards. The system can identify the drowsiness on the face of driver and can generate an alarm for them to stop or take necessary actions. Eye state analysis is a key step for alertness detection that helps to identify the state of the eye whether it is open or close. In this paper, the method has been proposed for eye state analysis following face and eye detection to detect driver’s alertness. This system has been integrated into a four-steps includes detection of face, detection of eye, analysis of eye state, and decision regarding driver's drowsiness. A warning signal has been buzzed on drowsiness detection to alarm the driver. Simulation results validate that our proposed idea attains high accuracy and low error rate as compared to state-of-art.
68-facelandmarks algorithm, Computer engineering. Computer hardware, Euclidean distance classifier, QA75.5-76.95, alertness monitoring system, drowsiness detection, alertness monitoring system, Euclidean distance classifier, 68-facelandmarks algorithm, TK7885-7895, Electronic computers. Computer science, T1-995, drowsiness detection, Technology (General)
68-facelandmarks algorithm, Computer engineering. Computer hardware, Euclidean distance classifier, QA75.5-76.95, alertness monitoring system, drowsiness detection, alertness monitoring system, Euclidean distance classifier, 68-facelandmarks algorithm, TK7885-7895, Electronic computers. Computer science, T1-995, drowsiness detection, Technology (General)
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