Today, a high proportion of traffic accidents are accidents caused by fatigue. A system is needed to warn drivers when they are tired or falling asleep. With this developed system, a system that monitors the driver’s eye conditions, understands driver fatigue and gives an audible warning has been developed. In this system, the Raspberry Pi 3B+ model is used, while the Raspberry Pi camera module is used to capture images and a speaker is used for audio. Python, OpenCV (Open Source Computer Vision Library, Open Source Computer Vision Library) and machine learning libraries were used to create the algorithm that understands driver fatigue. Haar Cascade classifier was used to detect eyes and faces, and whether the face was detected and whether the eyes were open or closed were determined. Fatigue was detected according to the time the eyes were closed, and an audible warning was given to the person.
