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International Journal for Research Trends and Innovation
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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
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Published Paper Details
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| Paper Title: | Drivers Drowsiness Detection System |
| Authors Name: | Dr. Nita Thakre , Pratham Tidke , Anishka Ilame , Shivam Pandey , Laxmi Gadhawe |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_189857
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| Published Paper Id: | IJRTI2405052 |
| Published In: | Volume 9 Issue 5, May-2024 |
| DOI: | |
| Abstract: | This paper proposes the driver fatigue detection system, which is the most required innovation in vehicle safety. It involves collecting sleep data from real drivers and using various AI algorithms and combinations to instantly improve performance. The system constantly monitors the driver's vital signs, facial expressions and driving behavior to detect early signs of fatigue. The importance of this study cannot be overstated as it directly addresses public safety issues related to drowsy driving. By providing real-time monitoring and timely alerts, this system can save countless lives, reduce the frequency of accidents, and reduce injuries on the road. The driver fatigue detection system is designed to reduce traffic accidents caused by driver fatigue. Secondary data collection for previous research on methods of testing sleepiness or driving. The goal is to provide a connection through which a program can capture the sleeping driver at the time of the accident and analyze the data, using images captured by webcams. This can be used to improve driving safety. There are three main stages of preparation: face detection, eye detection and sleep detection. Face detection detects the driver's eye field, which serves as a model for eye tracking in continuous frames. The visual image is then used to instantly wake up the detection and trigger the alarm. Image processing plays an important role in identifying the driver's face and eliminating eye fatigue. Drivers may fall asleep if they take cold medicine and other medications before driving. Fatigue occurs one hour after the flu vaccine. In response to the above problems, the author conducted research on computer vision, which can detect the driver who is not sleeping in real time using network surveillance cameras and then raise an alarm. In this study, sleep testing and eyelid monitoring were performed according to some factors that may affect the accuracy of fatigue detection, such as age, facial features, additional equipment and training equipment. |
| Keywords: | Driver’s fatigue, drowsiness, YOLO |
| Cite Article: | "Drivers Drowsiness Detection System", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.9, Issue 5, page no.363 - 368, May-2024, Available :http://www.ijrti.org/papers/IJRTI2405052.pdf |
| Downloads: | 000205136 |
| 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 |
| Publication Details: |
Published Paper ID: IJRTI2405052
Registration ID:189857
Published In: Volume 9 Issue 5, May-2024
DOI (Digital Object Identifier):
Page No: 363 - 368 Country: Nagpur, Maharashtra, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2405052 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2405052 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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