Paper Key : IRJ************171
Author: Mathumathi S,Rajeshwari P
Date Published: 06 Nov 2023
Abstract
Driver drowsiness is a critical factor contributing to road accidents, necessitating effective detection mechanisms to enhance road safety. This research paper investigates driver drowsiness detection using the Haar Cascade algorithm, a well-established computer vision technique. By focusing on analysing facial features and eye movements, this study proposes a reliable and efficient approach to monitoring driver alertness in real-time. The Haar Cascade algorithm is employed to detect facial landmarks and patterns associated with drowsiness. An essential contribution of this research is the customization of the algorithm to identify specific facial cues indicative of drowsiness, such as drooping eyelids and yawning. These cues are analysed collectively to determine the driver's level of attentiveness.
DOI LINK : 10.56726/IRJMETS45368 https://www.doi.org/10.56726/IRJMETS45368