Paper Title
Driver Mentality Detection System Using Deep Learning and Neural Networking

Abstract
Driver distraction is one of the major causes of accidents in the world. Detecting the distraction of the driver is one of the surest ways of measuring driver mentality. In this project, we have designed to build up a framework to identify driver’s tiredness, drowsiness, and unconsciousness to prevent accidents before happening with the help of Deep Learning and Neural Networking. At first, this model scans the driver’s face, then driver’s mentality is checked. If the driver is not in a good state, a warning will be given, then it starts checking driver's tiredness while driving further, if he/she feels sleepy for more than the predefined time, appropriate voice commands will be generated to keep the driver concentrated on driving. Keywords - Deep Learning, Neural Networking, Eigen Face Based Algorithm.