Paper Title
Computer Vision and Deeptech based Drowsy Driver detection and alert to avoid the road accidents
Article Identifiers
Authors
NEHA SHRIVAS , Dr VIVEK SHUKLA
Keywords
machine learning and deep learning
Abstract
Drowsy driving is one of the major causes of road accidents globally. As per the National Highway Traffic Safety Administration (NHTSA), drowsy driving causes around 100,000 accidents per year, resulting in around 1,500 fatalities and 40,000 injuries. This thesis proposes a real-time deep learning and machine learning-based system for drowsy driver detection and alert to avoid accidents. The system utilizes a combination of computer vision and machine learning techniques to monitor the driver's behavior and alert them in case of drowsiness.
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How To Cite (APA)
NEHA SHRIVAS & Dr VIVEK SHUKLA (February-2024). Computer Vision and Deeptech based Drowsy Driver detection and alert to avoid the road accidents. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(2), b62-b66. https://ijnrd.org/papers/IJNRD2402108.pdf
Issue
Volume 9 Issue 2, February-2024
Pages : b62-b66
Other Publication Details
Paper Reg. ID: IJNRD_213590
Published Paper Id: IJNRD2402108
Downloads: 000121978
Research Area: Computer Science & TechnologyÂ
Country: BILASPUR, CHHATTISGARH, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2402108.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2402108
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Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)
ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016
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This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition
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