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Deep Learning Based Driver Warning System Based on Face Features Recognition

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Intelligent Computing and Optimization (ICO 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 1167))

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Abstract

Drowsy driving poses significant risks, accounting for a quarter of car accidents. Involving inattentiveness and unconsciousness, it leads to 1,500 deaths, 71,000 injuries, and $12.5 billion in damages yearly. Drivers in Bangladesh are unwilling to obey the regulations while driving, and the majority of truck drivers are drug addicts. To address this, a continuous alarm system detecting drowsiness is required This research focuses on identifying drowsiness, unconsciousness, and agitation through facial expressions and eye movement analysis. Using deep learning, a camera records and analyzes each frame, alerting unfit drivers. The system integrates facial expressions for enhanced accuracy. Results confirm the system’s high precision, surpassing existing algorithms. Such systems offer a potential solution to mitigate drowsy driving’s grave consequences and improve road safety.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, East West University, Dhaka, 1212, Bangladesh

    Rakibul Huda, Al Azim Islam Khan Iram, Md. Muktadir Mukto, Fahadul Islam & Ahmed Wasif Reza

Authors
  1. Rakibul Huda
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  2. Al Azim Islam Khan Iram
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  3. Md. Muktadir Mukto
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  4. Fahadul Islam
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  5. Ahmed Wasif Reza
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Corresponding author

Correspondence to Ahmed Wasif Reza .

Editor information

Editors and Affiliations

  1. Modeling Evolutionary Algorithms Simulation and Artificial Intelligence,, Ton Duc Thang University, Ho Chi Minh City, Vietnam

    Pandian Vasant

  2. Department of Theoretical and Applied Mechanics, Russian University of Transport, Moscow, Russia

    Vladimir Panchenko

  3. Statistics and Operations Research, North West University, Mmabatho, South Africa

    Elias Munapo

  4. Faculty of Engineering Management, Poznań University of Technology, Poznań, Poland

    Gerhard-Wilhelm Weber

  5. UOW Malaysia KDU Penang University College, Penang, Malaysia

    J. Joshua Thomas

  6. Department of Informatics Engineering, Petra Christian University, Surabaya, Indonesia

    Rolly Intan

  7. Department of Computer Science and Engineering, Chittagong University of Engineering and Technology (CUET), Chittagong, Bangladesh

    Mohammad Shamsul Arefin

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Huda, R., Iram, A.A.I.K., Mukto, M., Islam, F., Reza, A.W. (2024). Deep Learning Based Driver Warning System Based on Face Features Recognition. In: Vasant, P., et al. Intelligent Computing and Optimization. ICO 2023. Lecture Notes in Networks and Systems, vol 1167. Springer, Cham. https://doi.org/10.1007/978-3-031-73318-5_33

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