DETECTION SYSTEM FOR DRIVER SAFETY

Detection system for driver safety is an enhanced technology that can help in prevention of accidents that are caused by motorists who fell asleep while driving the vehicle. The holy grail of this Python project is to build a drowsiness detection system that will detect that if a person’s eyes are closed for a few seconds or not. In this project we use OpenCV for gathering images from webcam. The approach we will be using for this python project is as follows: 1. Take image from camera as an input. 2.Detecttheface and create Region of Interest (ROI). 3.Detects the eyes from ROI and passit to classifier. 4.Classifier will categorize whether the eyes are closed or not. 5.Calculate score whether person is drowsy or not. Properties required for this project are: OpenCV, TensorFlow, Keras , Pygame. Output of our project will be that which we have built a drowsy driver alert system that you can implement in numerous ways. We have used OpenCV to detect face using a haar – cascade classifier a CNN (Convolutional Neural Network) model to predict the status. This project is used to address the real world problems such as drowsy driving by alerting drivers when they are sleepy, we can prevent accidents and make safer roads for everyone.