This paper is published in Volume-6, Issue-3, 2020
Area
Electronics and Communication Engineering
Author
N. Suresh
Co-authors
Gayam Akil, M. Gnana Adithya, B. Vijaya Krishna
Org/Univ
Koneru Lakshmaiah Educational Foundation, Vaddeswaram, Andhra Pradesh, India
Pub. Date
09 May, 2020
Paper ID
V6I3-1158
Publisher
Keywords
Drowsiness Detection, Advances Vehicle Safety, Eye Tracking System, Track The Location (GPS), Warning Output (Alarm and Led Blinking), Real-Time Drowsiness Detection

Citationsacebook

IEEE
N. Suresh, Gayam Akil, M. Gnana Adithya, B. Vijaya Krishna. Android application based vehicle driver drowsiness detection system through Image Processing, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
N. Suresh, Gayam Akil, M. Gnana Adithya, B. Vijaya Krishna (2020). Android application based vehicle driver drowsiness detection system through Image Processing. International Journal of Advance Research, Ideas and Innovations in Technology, 6(3) www.IJARIIT.com.

MLA
N. Suresh, Gayam Akil, M. Gnana Adithya, B. Vijaya Krishna. "Android application based vehicle driver drowsiness detection system through Image Processing." International Journal of Advance Research, Ideas and Innovations in Technology 6.3 (2020). www.IJARIIT.com.

Abstract

Conduct the simulation experiment and analyze the data to search for an automatic detection system based on driver performance, human conduct, and emotions. A design of drowsiness detection systems is the goal of this venture. A driver with a Drowsy or sleepy mode can not tell when an uncontrolled sleep will take place. Injury crashes in fall asleep are very grave. Accompanying fatigue or drowsiness- related crashes[1] can result in 1.200 deaths and 77.000 injuries per year in recent statistics. Driver fatigue is responsible for more than 25 percent of road accidents[2]. Through alert the driver about his / her drowsiness, we will can the risk of an accident. The main concept of this system is the simulation of somnolence detection with image processing and the detection of somnolence. Furthermore, the person authorized to locate the vehicle can be notified by GPS. This system helps avoid most injuries, thereby protecting human lives and increasing personal suffering. With this system, the car driver's eyes are monitored by camera, and we detect driver drowsiness symptoms early enough to avoid accidents by developing an algorithm. Within a specified time interval the car driver's eyes are closed by more than80 percent. This project will help in advance in detecting driver fatigue and give alarming signals in the form of a sound and an LED blinking. The alarm is manually not immediately deactivated. A deactivation key is used to trigger the alert for this reason. The machine assumes that the operator sleeps and sends a warning message.
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