Drowsiness detection of the cars driver using the Raspberry Pi based on image processing

Abstract

Drowsiness while driving is one of the biggest factors causing traffic accidents. To prevent this, it is necessary to make an automatic system that can detect the drowsiness of vehicle drivers. In this research, the driver's face and eye positions were detected using a camera and processed using a Raspberry Pi. The position of the face and eyes was obtained using the Viola Jones method and then continued with determining the condition of the driver's eyes. The number of frames processed per second is set to 5 frames, so as not to burden the computation. The research was conducted on the object of the driver with glasses and without glasses by placing the camera at a distance of 20 to 80 cm from the driver. The study was conducted indoors and in the car cabin with lighting intensity between 0 to 100 Lux. In this study, eye position detection reached 100% at an illumination intensity of 20 to 100 Lux with a camera distance of 20 to 80 cm for drivers without glasses and an illumination intensity from 20 to 60 for drivers with glasses. Drowsiness condition is determined if three consecutive frames are detected when the eyes are closed.