This paper is published in Volume-5, Issue-2, 2019
Area
Transportation
Author
Bapathu Ramakrishna Reddy
Co-authors
Bitragunta Lakshmi Durga Pratyusha, Chakicherla Bala Sai Vagdevi, Annapureddy Venkata Ajaya Kumar Reddy, Ajay Rahul Hari
Org/Univ
NRI Institute of Technology, Vijayawada, Andhra Pradesh, India
Pub. Date
06 April, 2019
Paper ID
V5I2-1769
Publisher
Keywords
Face Detection, Locating Eyes, Eye-Aspect Ratio, Security, Drowsiness

Citationsacebook

IEEE
Bapathu Ramakrishna Reddy, Bitragunta Lakshmi Durga Pratyusha, Chakicherla Bala Sai Vagdevi, Annapureddy Venkata Ajaya Kumar Reddy, Ajay Rahul Hari. Nap detection and alert system using OpenCV, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Bapathu Ramakrishna Reddy, Bitragunta Lakshmi Durga Pratyusha, Chakicherla Bala Sai Vagdevi, Annapureddy Venkata Ajaya Kumar Reddy, Ajay Rahul Hari (2019). Nap detection and alert system using OpenCV. International Journal of Advance Research, Ideas and Innovations in Technology, 5(2) www.IJARIIT.com.

MLA
Bapathu Ramakrishna Reddy, Bitragunta Lakshmi Durga Pratyusha, Chakicherla Bala Sai Vagdevi, Annapureddy Venkata Ajaya Kumar Reddy, Ajay Rahul Hari. "Nap detection and alert system using OpenCV." International Journal of Advance Research, Ideas and Innovations in Technology 5.2 (2019). www.IJARIIT.com.

Abstract

In recent years driver fatigue is one of the major causes of vehicle accidents in the world. A direct way of measuring driver fatigue is measuring the state of the driver i.e. drowsiness. So it is very important to detect the drowsiness of the driver to save life and property. This project is aimed towards developing a prototype of a drowsiness detection system. This system is a real-time system which captures image continuously and measures the state of the eye according to the specified algorithm and gives a warning if required. Though there are several methods for measuring the drowsiness, this approach is completely non-intrusive which does not affect the driver in any way, hence giving the exact condition of the driver. For detection of drowsiness eye aspect ratio value of the eye is considered. So when the closure of eye exceeds a certain amount then the driver is identified to be sleepy. Corrections for drowsiness include both in and out vehicle alarms and its repetition turns the engine off after giving a signal to the vehicles behind. We are also providing security for the owner i.e., if the vehicle is driven by another person and does any kind of suspicious activities then ,not the actual person but the owner will face problems, in order to avoid the problem for the owner, when the engine starts we automatically capture the image of the driver along with date and time without knowledge of the driver. Then he can easily identify the person who is driving and the owner will be saved.
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