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Paper Details
Paper Title
Drowsiness and Yawn Detection System
Authors
Mrs. Yasmeen Sultana, Atif AHmed, Syed Taqi Uddin, Syed Idris
Abstract
Various investigations show that drivers' Drowsiness and fatigue are one of the leading causes of road accidents. The current technology in a digital computer system allows researchers worldwide to study fatigue behavior. This study aims to detect the Drowsiness in drivers to prevent accidents and improve the safety on the highways. Real-time face detection is implemented to locate the driver's face region. Driver's fatigue impacts the alertness and response time of the drivers and increases the chances of being involved in car accidents. National Highway Traffic Safety Administration (NHTSA) analysis data indicates that driving while Drowsiness contributes to 22 to 24 percent of car crashes. Driving while drowsily results in 4-6% higher near-crash/crash risk relative to alert drivers.
This high accident rate is because sleepy drivers fail to take corrective actions before a collision. A vital irony in driver's fatigue is that the driver may be too tired to realize his level of Drowsiness. The driver often ignores this critical problem. Therefore, assisting systems that monitor a driver's level of vigilance is crucial to preventing road accidents. These systems should then alert the driver in the case of Drowsiness or inattention.
In this paper, we study whether drivers' eyes remain closed for more than a certain period; drivers are drowsy, and an alarm is sounded. Yawn similarly is detected when a person yawns several times. The programming is done in python language and Open CV using the Haar cascade library and shape predictor library for the detection of facial features and yawning detection.
Keywords- Drowseness Detection and Yawn Detection
Publication Details
Unique Identification Number - IJEDR2202028Page Number(s) - 165-171Pubished in - Volume 10 | Issue 2 | June 2022DOI (Digital Object Identifier) - Publisher - IJEDR (ISSN - 2321-9939)
Cite this Article
Mrs. Yasmeen Sultana, Atif AHmed, Syed Taqi Uddin, Syed Idris, "Drowsiness and Yawn Detection System", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.10, Issue 2, pp.165-171, June 2022, Available at :http://www.ijedr.org/papers/IJEDR2202028.pdf
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