AN EMBEDDED SYSTEM FOR DRIVER DROWSINESS DETECTION

Abstract

Our project titled “An Embedded System for Driver Drowsiness Detection” which aimed towards developing a real-time embedded system that detects driver drowsiness. A direct way of measuring driver fatigue is to measure the state of driver drowsiness. This system which captures image continuously and measures the state of the eye. For drowsiness detection, we considered the closure value of the eye. When the closure of eye crosses threshold value for a certain period of time then the driver is identified to be sleepy. To build the prototype we use Raspberry-pi, Camera, Audio Module. This system has several OpenCV libraries, dlib library and the method we are using is eye aspect ratio and facial landmark localization. To localize facial structure, we use facial landmark and using eye aspect ratio we can get the closure value of the eye. We use multiple software such as Raspbian Operating System, Python IDLE, CMake, Advance IP Scanner, MobaXterm to develop this system.