EconPapers    
Economics at your fingertips  
 

Fatigue Driver Alert System

Mallikarjun M Kodabagi, Afrah Ayub, Mahima Bk, Shruthi Siva and Apurva Korni

International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2024, vol. 10, issue 2, 735-740

Abstract: The rise in accidents caused by drivers who are too sleepy to drive has made advanced driver alert systems necessary. This research proposes a novel method for identifying drowsy drivers through the integration of GPS technology and physiological data, offering an inventive solution to this pressing problem. We explore the complexities of drowsiness detection, highlighting the difficulties and introducing an improved approach to improve performance. Using real-time GPS data, our system not only warns drivers when something is wrong, but it also suggests appropriate rest spots depending on the driver's present location. Our method, which emphasizes proactive measures to limit the risks associated with drowsy driving, pioneers safer driving habits by seamlessly combining physiological measurements, GPS technology, and algorithmic enhancements. Performance assessments show encouraging outcomes, highlighting the potential advantages and importance of these devices in lowering driver fatigue-related incidents. This research advances vehicle safety and emphasizes the need of taking preventative action to reduce the risks associated with sleepy driving.

Keywords: Drowsy Driving; Alertness Monitoring; Drowsiness Prevention (search for similar items in EconPapers)
Date: 2024
Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT24102112
References: Add references at CitEc
Citations:

Downloads: (external link)
https://ijsrcseit.com/home/article/view/CSEIT24102112 Article URL (text/html)
https://ijsrcseit.com/home/article/download/CSEIT24102112/CSEIT24102112 Full text (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:jbh:ijsrcs:v10:y2024:i2:id:154

DOI: 10.32628/CSEIT24102112

Access Statistics for this article

More articles in International Journal of Scientific Research in Computer Science, Engineering and Information Technology from International Journal of Scientific Research in Computer Science, Engineering and Information Technology
Bibliographic data for series maintained by Pankaj Sharma (USA) ().

 
Page updated 2026-09-18
Handle: RePEc:jbh:ijsrcs:v10:y2024:i2:id:154