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.
