CNN Based Driver Drowsiness Detection System Using Emotion Analysis

The drowsiness of the driver and rash driving are major causes road accidents, which result in loss valuable life, deteriorate safety traffic. Reliable precise systems required to prevent accidents improve traffic safety. Various detection have been designed with different technologies an affinity towards unique parameter detecting driver. This paper proposes a novel model multi-level distribution using Convolution Neural Networks (CNN) followed by emotion analysis. analysis, this proposed model, analyzes driver’s frame mind identifies motivating factors for patterns. These patterns were analyzed based on acceleration system, speed vehicle, Revolutions per Minute (RPM), facial recognition pattern is treated 2D Network detect behavior emotion. implemented OpenCV experimental results prove that detects more effectively than existing technologies.