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Research Article

Driver Drowsiness Detection System

  • Paper ID 605
  • Volume 3, Issue 6
  • Pages 122-125
  • Published Online: November-December 2022
  • 12 Views
Open Access Peer Reviewed

Authors

  • Anubhav pandey1
  • Ankur Singh2
  • Aditya Singh3
  • Ajay Kumar4

123 Student, Department of Computer Science and Engineering, ITM Gida Gorakhpur, Uttar Pradesh, India. 4Assistant Professor, Department of Computer Science and Engineering, ITM Gida Gorakhpur, Uttar Pradesh, India.

Article Information

DOI
No DOI
Published Online
November-December 2022
Pages
122-125
Article Type
Research Article
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No DOI available for cross-reference

References

[1]. Akrout B. Mahdi W.: ‘Spatio-temporal features for the automatic control of driver drowsiness state and lack of concentration’, Mach. Vis. Appl., 2015, 26, (1), pp. 1– 13
[2]. “Eye tracking based driver fatigue monitoring and warning system”, IEEE IICPE, New Delhi, India, Jan. 2014 H. Singh, J. S. Bhatia, and J. Kaur.
[3]. OyiniMbouna R. Kong S.G. Chun M.-G.: ‘Visual analysis of eye state and head pose for driver alertness monitoring’, IEEE Trans. Intell. Transp. Syst., 2013, 14, (3), pp. 1462– 1469
[4]. World Health Organization. Road Safety: Basic Facts.; 2016 (http://www.who.int/violence_injury_prevention/publications/road_traffic/Road_safety_media _brief_full_document.pdf).
[5]. Degada and V. Savani (2015). An Embedded Technology and ICT Approach to the Design and Implementation of a Low-Cost, Portable Telemedicine System The 5th Nirma University International Conference on Engineering (NUICONE) was held in 2015. (page1 - 6). IEEE, Ahmedabad, India.
[6]. Bergasa L.M. Nuevo J. Sotelo M.A. et al.: ‘Real-time system for monitoring driver vigilance’, IEEE Trans. Intell. Transp. Syst., 2006, 7, (1), pp. 63– 77
[7]. "Squeezenet: Alexnetlevel accuracy with 50x scaling," F. N. Iandola, S. Han, M. W. Moskewicz, K. Ashraf, W. J. Dally, and K. Keutzerpp. 1-13 in Proceedings of the International Conference on Learning Representations, 2017
[8]. P. Kang, Y. Wei, and Z. Wei (2017). Based on Embedded Networking and Qt Technology, this control system for granary ventilation. The 29th Chinese Control and Decision Conference (CCDC) was held in 2017. (Pages 2275 - 2280). IEEE, Chongqing, China.
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