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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | Drowsiness Detection Using Machine Learning and Open CV |
| Authors Name: | Aditya Raj Gupta , Anupam Joshi , Agraj Sharma , Sandeep Kumar |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_187336
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| Published Paper Id: | IJNRD2304491 |
| Published In: | Volume 8 Issue 4, April-2023 |
| DOI: | |
| Abstract: | A safety tool called drowsiness detection can stop accidents from being caused by drivers who nodded off behind the wheel. Drowsy driving is one of the main factors that contributes to tragic road accidents, which claim the lives of many people every year. Drivers who are sleep deprived cause close to 50% of traffic accidents. This project's goal is to warn the driver if drowsiness is found.[15] A system that employs Python, OpenCV, and cameras to inform the user when they nod off can be created to prevent these kinds of incidents. The project's first aim is to increase the driver's safety. The device will monitor the driver's eyes and recognise blinking by use of an in-car camera that will be fitted. The device will detect tiredness and sound an alarm to inform the driver if the driver's eyes are closed for longer than a predetermined amount of time. In order to prevent accidents brought on by driver fatigue and napping, this paper provides a summary of the computer engineering research done to develop a system for detecting driver drowsiness. The study included conclusions and suggestions for the project's limited use of the different methodologies. While the project's execution offers a useful understanding of the system's operation and the modifications that may be made to raise the utility of the system as a whole. In order to promote future optimization in the relevant region and create the utility with higher efficacy for a safer road, the study also summarises the authors' views.[16] |
| Keywords: | eye detection, blink pattern, fatigue, Driver drowsiness, blink pattern. |
| Cite Article: | "Drowsiness Detection Using Machine Learning and Open CV", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 4, page no.e683-e689, April-2023, Available :http://www.ijnrd.org/papers/IJNRD2304491.pdf |
| Downloads: | 000118751 |
| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 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:IJNRD2304491 Registration ID: 187336 Published In: Volume 8 Issue 4, April-2023 DOI (Digital Object Identifier): Page No: e683-e689 Country: GREATER NOIDA, Uttar Pradesh, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2304491 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2304491 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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