Intelligent-Drive-Assistance-System

This project proposes a non-intrusive approach for detecting drowsiness in drivers, using Computer Vision. Developing various technologies for monitoring and preventing drowsiness while driving is a major trend and challenge in the domain of accident avoidance systems. Haar face detection algorithm is used to capture frames of image as input and then the detected face as output. Therefore, in this paper, a light-weight, real time driver’s drowsiness detection system is developed. The system records the videos and detects driver’s face in every frame by employing image processing techniques. The system is capable of detecting facial landmarks, computes Eye Aspect Ratio (EAR) and Eye Closure Ratio (ECR) to detect driver’s drowsiness based on adaptive thresholding. Whereas the implementation of the project give the real world idea of how the system works and what changes can be done in order to improve the utility of the overall system. Furthermore, the paper states the overview of the observations made by the authors in order to help further optimization in the mentioned field to achieve the utility at a better efficiency for a safer road. A person driving needs to be able to focus on driving at all instances. Any prolonged or sudden complications to the person driving the vehicle can cause serious accidents/damages.