Issue |
E3S Web Conf.
Volume 399, 2023
International Conference on Newer Engineering Concepts and Technology (ICONNECT-2023)
|
|
---|---|---|
Article Number | 01006 | |
Number of page(s) | 9 | |
Section | Electronics and Electical Engineering | |
DOI | https://doi.org/10.1051/e3sconf/202339901006 | |
Published online | 12 July 2023 |
Smart Safety and Accident Prevention System
1 Associate Professor, Department of ECE, KPR Institute of Engineering and Technology, Coimbatore, Tamil Nadu, India
2 UG Scholar, Department of ECE, KPR Institute of Engineering and Technology, Coimbatore, Tamil Nadu, India
* Corresponding author: muralidharanae@gmail.com
The primary cause of road accident results in fatalities, serious injuries and monetary losses is known to be due to drowsy or sleepy drivers, according to analysis reports on recent traffic accidents. Lack of sleep, medication, drugs, or prolonged driving contributes to drowsiness. A system that can identify a driver’s drowsy state and warn him before an accident occurs is required to avoid roadside accidents caused by distracted driving. Many researchers have recently expressed their interest in drowsiness detection. The methods essentially involve monitoring the driver’s physiological or behavioral 1summarizes some of the most recent methods put forth in this field is given. We propose an algorithm to monitor eye blinks that uses eye feature points to determine whether the eye is open or closed and sets off an alarm if the driver is drowsy. In-depth experimental results are also provided to highlight the benefits and drawbacks of the proposed method.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.