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1705576 Vol 7 · Issue 9 Download Paper

Alertness Assured: Sleep Detection and Video Control Technology

Akhil Ahmed Shreyash A. Nerkar Mahesh Upadhyay Devang Prabhune Kusumlata Pawar

Subject area: Science,Engineering and Technology  ·  Area of research: Artificial Intelligence

Abstract

This paper introduces a comprehensive solution for sleep detection in automotive and entertainment settings, integrating an adaptive play/pause system for multimedia?s like video content to enhance safety and user experience. Employing Python for implementation, the system utilizes computer vision techniques to monitor driver facial features and movements in real-time, ensuring vigilance on the road. Concurrently, it extends its functionality to entertainment environments, seamlessly integrating with multimedia files like videos to fetch metadata and playback controls. Upon detecting sleep, the system automatically pauses playback, prioritizing sleep and minimizing distractions, thereby promoting safety without compromising user experience. In conclusion, this multi-platform approach offers a holistic solution to address safety concerns across automotive and entertainment domains.

Keywords

Sleep detection, Computer vision, Facial landmarks, Real-time monitoring, Video Content.

References

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[2] Muhammad Ramzan, Hikmat Ullah Khan, Shahid Mahmood Awan, Amina Ismail, Mahwish Ilyas and Ahsan Mahamood—A Survey on State-of-the-Art Drowsiness Detection Techniques,‖ IEEE Access. vol. 7, May 2019.

[3] R Kannan, Palamakula Jahnavi, M Megha, ―Driver Drowsiness Detection and Alert System,‖ ICICACS . 5/23/$31.00.

[4] Ioana-Raluca Adochiei, Oana-Lsabela STIRBU, Narcis-Iulian, Matei Pericle-Gabriel, Ciprian- Marius larco, Stefan-Mircea Mustata, Diana Costin—Driver’s Drowsiness Dectection and warning Systems for Critical Infrastructures,‖ IEEE , October 2020.

[5] Amin Azizi Suhaiman, Zazilah May and Noor A’ in A.Rahman —Development of an intelligent drowsiness detection system for drivers using image processing technique,‖ IEEE SCOReD, 2020.

[6] Burcu Kir Savas and Yasar Becerikli —Real Time Driver Fatigue Detection System Based on Multi-Task ConNN, ‖ IEEE ACCESS, 2020.

[7] Inakollu Kiran KUnar, Vipul Agarwal and Munnangi Siva Reddy—Image Recognition Based Driver Drowsiness Detection using Python, ‖ ICEARS 2022 , 5/20/$31.00, October 2020.

[8] Ana-Mari Baiasu and Catalin Dumitrescu— Contributions to driver fatigue dectetion based on eye-tracking,‖ IJCSSP ,

[9] Venkata Rame Reddy Chirra, Srinivasu;u Reddy Uyyala and Venkata Krishna Kishore Kolli— Deep CNN: A Machine Learning Approch For Driver Drowsiness Dectection Based on Eye State ,‖ IEEE , November 2019.

[10] Suporn Pongnumkul, Mira Dontcheva, Wilmot Li and Michael Cohen—Pause and play: Automatically Linking Screencast Video Tutorials with Application ,‖ ResearchGate 10.1145/2047196.2047213, November 2019

How to cite this paper

Akhil Ahmed, Shreyash A. Nerkar, Mahesh Upadhyay, Devang Prabhune, Kusumlata Pawar "Alertness Assured: Sleep Detection and Video Control Technology" Iconic Research And Engineering Journals Volume 7 Issue 9 2024 Page 79-82
Akhil Ahmed, Shreyash A. Nerkar, Mahesh Upadhyay, Devang Prabhune, Kusumlata Pawar "Alertness Assured: Sleep Detection and Video Control Technology" Iconic Research And Engineering Journals, vol. 7, no. 9, Mar. 2024
Akhil Ahmed, Shreyash A. Nerkar, Mahesh Upadhyay, Devang Prabhune, Kusumlata Pawar (2024). Alertness Assured: Sleep Detection and Video Control Technology. Iconic Research And Engineering Journals, 7(9).
Akhil Ahmed, Shreyash A. Nerkar, Mahesh Upadhyay, Devang Prabhune, Kusumlata Pawar "Alertness Assured: Sleep Detection and Video Control Technology" Iconic Research And Engineering Journals, vol. 7, no. 9, Mar. 2024.
@article{1705576,
      author = {Akhil Ahmed, Shreyash A. Nerkar, Mahesh Upadhyay, Devang Prabhune, Kusumlata Pawar},
      title = {Alertness Assured: Sleep Detection and Video Control Technology},
      journal = {Iconic Research And Engineering Journals},
      year = {2024},
      volume = {7},
      number = {9},
      pages = {79-82},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1705576.pdf},
      abstract = {This paper introduces a comprehensive solution for sleep detection in automotive and entertainment settings, integrating an adaptive play/pause system for multimedia?s like video content to enhance safety and user experience. Employing Python for implementation, the system utilizes computer vision techniques to monitor driver facial features and movements in real-time, ensuring vigilance on the road. Concurrently, it extends its functionality to entertainment environments, seamlessly integrating with multimedia files like videos to fetch metadata and playback controls. Upon detecting sleep, the system automatically pauses playback, prioritizing sleep and minimizing distractions, thereby promoting safety without compromising user experience. In conclusion, this multi-platform approach offers a holistic solution to address safety concerns across automotive and entertainment domains.},
      keywords = {Sleep detection, Computer vision, Facial landmarks, Real-time monitoring, Video Content.},
      month = {March},
  }