Driver's lethargy is one of the main causes of car accidents nowadays. We have discussed fatigue, object detection in hand, head pose estimation and siesta detection. This paper is focused on extracting and analyzing the various factors to alert the driver while driving the car. We have implemented real time face detection by using CNN. We have used light forbearance model as it will be easy to implement in real time situation. Eye tiredness by calculating percentage of eyelid closure over the pupil (PERCLOS), object detection in hand by tensor flow. Object is detected when the driver uses mobile phone and/or holds substance abuse material while driving. Mouth geometric movement detection is implemented by Deep Neural Network. This aims to reduce road accidents and the loss of life. In every 25 second a person dies in road accidents. We have proposed a method to reduce accidents by implementing certain factors. This will alert us whether or not the driver is in the proper condition for driving.
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