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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: | SLEEP ALERT SYSTEM FOR DRIVERS |
| Authors Name: | vedant sharma |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_201067
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| Published Paper Id: | IJNRD2307080 |
| Published In: | Volume 8 Issue 7, July-2023 |
| DOI: | http://doi.one/10.1729/Journal.35115 |
| Abstract: | The primary goal of this project was to create a system that can monitor the state of a person's eyes in real-time using computer vision and deep learning techniques. The main focus was on determining whether the eyes were open or closed, with practical applications in detecting driver drowsiness and monitoring fatigue levels to enhance safety and alertness. The project followed a systematic approach that commenced with gathering and preparing a dataset of eye images. To build the model, transfer learning was employed, utilizing the InceptionV3 model as the base and incorporating additional layers for classification. The model was trained using data augmentation techniques and optimized with the Adam optimizer and categorical cross-entropy loss function. For real-time monitoring, the system implemented face and eye detection algorithms to identify the specific area of interest containing the eyes in each frame. By tracking the duration of open or closed eyes, the system triggered an alarm if the eyes remained closed for an extended period, indicating potential drowsiness or fatigue. Although the monitoring system was successfully developed and implemented, future enhancements could involve incorporating more diverse datasets, refining the model architecture, and optimizing the detection algorithms. Overall, this project serves as a demonstration of the capabilities of computer vision and deep learning in eye state monitoring, opening up possibilities for further research and applications in safety and attention tracking domains. |
| Keywords: | machine learning, ANN, CNN, jupyterlab, Keras, haar cascade, classifier, Adam optimizer, RELU, Softmax, Pre-processing, OpenCV, inceptionV3, VGGNet, RESnet |
| Cite Article: | "SLEEP ALERT SYSTEM FOR DRIVERS", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 7, page no.a638-a652, July-2023, Available :http://www.ijnrd.org/papers/IJNRD2307080.pdf |
| Downloads: | 000118755 |
| 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:IJNRD2307080 Registration ID: 201067 Published In: Volume 8 Issue 7, July-2023 DOI (Digital Object Identifier): http://doi.one/10.1729/Journal.35115 Page No: a638-a652 Country: vidisha , Madhaya Pradesh, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2307080 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2307080 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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