DRIVER SLEEPINESS RECOGNITION FRAMEWORKUTILIZING OPEN CV ALGORITHM

Abstract

— In many countries throughout the world,
driver sleepiness is a major cause of traffic accidents.
Several driver sleepiness detecting technologies have
been presented in recent years to help alleviate this issue.
The OpenCV (Open-source Computer Vision) algorithm
is used in this work to introduce a unique method for
detecting driver sleepiness. To record real-time video
frames of the driver's face, the suggested system makes
use of a camera installed inside the car. Applying the
OpenCV method,face characteristics are analyzed to look
for indicators of sleepiness. The method consists of a
number of steps, including face detection, facial
landmark identification, and eye tracking. The driver's
face is found in the video frames that were collected
using a cascade classifier in the face detection stage. In
thefollowing step, a trained facial landmark recognition
model is used to identify face landmarks. The technology
analyzes the driver's eye closure patterns, a key sign of
fatigue, by following the movement of particular facial
markers. Extensive testing was doneon a large dataset of
drivers who displayed different levels of tiredness in
order to assess how well the suggested system performed.
The outcomes illustrate the system's efficacy in precisely
and reliably identifying driver sleepiness with high recall
rates. Through early notifications to sleepy drivers and
the prevention of accidents brought on by driver
weariness, the driver drowsiness detection system
utilizing the OpenCV algorithm described in this
research has the potential to improve road safety. The
device may be integrated into current cars or added to
advanced driver assistance systems (ADAS) to increase
general road safety and lower the likelihood of accidents
brought on by drowsy driving.