Contributions to driver fatigue detection based on eye-tracking

In recent years, one of the most important factors in road accidents is the drowsiness of drivers and the distraction while driving. In this paper, we describe a system that monitors the detection of fatigue or drowsiness. The proposed solutions follow the driver's gaze, and if the system identifies the closed eyes, it triggers an alarm signal intended to alert against losing control of the car and causing traffic accidents. Eye-tracking is the process that measuring the eye position and eye movement. The proposed method is structured in three phases. In the first phase, eye images are captured at constant time intervals and converted into grayscale images. In the second phase these images are fed to Haar algorithm to identify the driver eyes. In the third phase, based on the previous phase the system can now take action to continue monitoring or trigger alarm to alert the driver if the drowsiness has been detected. © 2021, North Atlantic University Union NAUN. All rights reserved.