Accident alert system
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Date
2021-05
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Publisher
AIKTC
Abstract
Nowadays, Driver drowsiness is one of the major cause for most of the accidents
in the world. Detecting the driver eye tiredness is the easiest way for measuring
the drowsiness of driver. The existing systems in the literature, are providing slightly
less accurate results due to low clarity in images and videos, which may result due
to variations in the camera positions.
In order to solve this problem, a driver drowsiness detection system is proposed
in this paper, which makes use of eye blink counts for detecting the drowsiness.
Specifically, the proposed framework, continuously analyzes the eye movement of
the driver and alerts the driver by activating the vibrator when he/she is drowsy.
When the eyes are detected closed for too long time, a vibrator signal is generated
to warn the driver. The experimental results of the proposed system, which is implemented
on Open CV and Raspberry Pi environment with a single camera view,
illustrate the good performance of the system in terms of accurate drowsiness detection
results and thereby reduces the road accidents.
Keywords: Drowsiness, Fatigue Detection, Raspberry Pi, Image Processing, Eye
Detection, EAR
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