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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 118
Article Submitted : 21686
Article Published : 8549
Total Authors : 22487
Total Reviewer : 811
Total Countries : 159
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| Paper Title: | Study on Driver drowsiness Detection |
| Authors Name: | Anush Kulal M , Arya Sinha , Dr.Kamalraj R |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_202876
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| Published Paper Id: | IJRTI2505010 |
| Published In: | Volume 10 Issue 5, May-2025 |
| DOI: | |
| Abstract: | Ensuring road safety is a critical priority in modern transportation systems, and advanced driver assistance technologies have become integral to reducing accidents caused by driver fatigue. With continuous advancements in artificial intelligence, image processing, and sensor technology, contemporary vehicles are now equipped with intelligent systems that can monitor a driver's physiological and behavioural cues to enhance driving safety. This paper presents a comprehensive review of existing research on driver drowsiness detection and alert mechanisms, with a focus on enhancing accuracy and reliability. Our study employs the Euclidean distance method to analyse eye and facial movements using real-time data from camera sensors. By continuously tracking key indicators such as blink rate, eye closure, and yawning frequency, the system effectively identifies early signs of fatigue. Recent developments in video processing and machine learning algorithms have significantly improved the precision of image analysis, enabling more accurate detection of drowsiness. The Driver Drowsiness Detection System plays a crucial role in mitigating sleep-related traffic accidents, particularly in regions where fatigue-related crashes are prevalent. In this research, we propose an optimized feature extraction method that accurately assesses driver fatigue by analyzing the relative positions and movements of the eyes and mouth. By integrating advanced image processing techniques with real-time monitoring, this system aims to provide timely alerts, thereby improving driver awareness and reducing the risk of accidents. |
| Keywords: | Euclidean distance, Driver drowsiness detection, Facial Detection using Open CV’s Haar Cascade, Sound Alert. |
| Cite Article: | "Study on Driver drowsiness Detection", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 5, page no.a112-a114, May-2025, Available :http://www.ijrti.org/papers/IJRTI2505010.pdf |
| Downloads: | 0001265 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2505010
Registration ID:202876
Published In: Volume 10 Issue 5, May-2025
DOI (Digital Object Identifier):
Page No: a112-a114 Country: Bangalore, karnataka, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2505010 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2505010 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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