Bus Driver Distraction Detection using Machine learning
Pages : 929-932
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Abstract
In this system, we proposed to condense the number of visual designs caused by driver’s fatigue and thus progress road safety. This system focuses detection of driver’s unconsciousness/inertness based on optical information and artificial intelligence. We locate, capture and analyze both, face and eyes of driver to measure PERCLOS (percentage of eye closure) with Softmax for neural transfer function. It will be also observe alcoholic symptoms & pulse throbbing to check out whether the individual is normal or abnormal. Driver’s fatigue is one of the most important causes of traffic accidents, supreme for drivers of large vehicles (such as automobiles and heavy trucks) due to elongated driving periods and monotony in occupied situations.
Keywords: Fatigue detection, Haar Cascade Algorithm, openCV, feature extraction, etc.