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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 System: Stay Alert Stay Alive |
| Authors Name: | Pranit Narendra Muttha , Siddharth Mohan Lanke , Abhishek Vanshiv , Saishubham Laisetti , Swati Joshi |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_208266
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| Published Paper Id: | IJNRD2311071 |
| Published In: | Volume 8 Issue 11, November-2023 |
| DOI: | |
| Abstract: | Drowsiness detection systems are pivotal in enhancing safety across various operational domains, particularly in transportation and critical operations. This research project aims to develop a cost-effective and highly efficient software-based drowsiness detection system, utilizing deep learning techniques, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs). The primary objective is to identify and mitigate the risks associated with fatigue by detecting behavioral indicators of drowsiness, issuing timely alerts, and potentially triggering interventions to ensure safety.This project emphasizes real-time drowsiness detection without the need for additional hardware, making it accessible and adaptable across various platforms and devices. The system's efficiency in recognizing drowsiness indicators and the avoidance of costly sensors and equipment align with the project's core goals.The research is inspired by notable contributions in the field, including advancements in driver drowsiness detection and real-time monitoring systems. By addressing the critical issue of drowsiness and fatigue, this project aspires to make the world a safer place by reducing accidents, saving lives, and enhancing productivity. Ultimately, the software-based drowsiness detection system has the potential to offer a low-cost and effective solution for a wide range of applications, from individual users to large-scale commercial and industrial operations, and contribute to a safer and more efficient world. |
| Keywords: | Drowsiness, Detection, Fatigue, Safety, Collision. |
| Cite Article: | "Drowsiness Detection System: Stay Alert Stay Alive", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 11, page no.a645-a647, November-2023, Available :http://www.ijnrd.org/papers/IJNRD2311071.pdf |
| Downloads: | 000118772 |
| 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:IJNRD2311071 Registration ID: 208266 Published In: Volume 8 Issue 11, November-2023 DOI (Digital Object Identifier): Page No: a645-a647 Country: Pune, Maharashtra, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2311071 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2311071 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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