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Drunk Driving and Drowsiness Detection Alert System

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Proceedings of the International Conference on ISMAC in Computational Vision and Bio-Engineering 2018 (ISMAC-CVB) (ISMAC 2018)

Part of the book series: Lecture Notes in Computational Vision and Biomechanics ((LNCVB,volume 30))

Abstract

Advancement of safety features to avert drunk and drowsy driving has been one of the leading technical challenges in the automobile business. Especially in this modern age where people are under serious work pressure has led to higher crash rates. To prevent such accidents this paper discusses the use of nonintrusive techniques by using visual features to determine whether driver is driving in alert state. Drowsiness detection has been implemented using HAAR Cascade for face and eye closure detection and yawn detection implemented using Template matching in visual studio 2013. For drunk state detection, an alcohol sensor (MQ-3) has been implemented to avoid drunk driving. If the driver is found to be in drunk or drowsy condition, then an alarm would be generated and the driver being alerted using a buzzer and a vibrator that can be placed in the seatbelt or under driver seat thus preventing from mishaps taking place.

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References

  1. Kaplan S, Guvensan MA, Yavuz AG, Karalurt Y (2015) Driver behavior analysis for safe driving: a survey. IEEE Trans Intell Transp Syst 16(6):3017–3032

    Article  Google Scholar 

  2. Mbouna RO, Kong SG, Chun M-G (2013) Visual analysis of eye state and head pose for driver alertness monitoring. IEEE Trans Intell Transp Syst 14(3):1462–1469

    Article  Google Scholar 

  3. Omidyeganeh M, Shirmohammadi S, Abtahi S, Khurshid A, Farhan M, Scharcanski J, Hariri B, Laroche D, Martel L (2016) Yawning detection using embedded smart cameras. IEEE Trans Instrum Meas 65(3):570–582

    Article  Google Scholar 

  4. Chacon-Murguia MI, Prieto-Resendiz C (2015) Detecting driver drowsiness: a survey of system designs and technology. IEEE Consum Electron Mag 4(4):107–119

    Article  Google Scholar 

  5. Sivakumar T, Krishnaraj R (2012) Road traffic accidents (Rtas) due to drunken driving in India challenges in prevention. IRACST—Int J Res Manag Technol (IJRMT) 2(4):401–406

    Google Scholar 

  6. Bhandari GM, Durge A, Bidwai A, Aware U (2014) Yawning analysis for driver drowsiness detection. IJRET: Int J Res Eng Technol 3(2):502–505

    Article  Google Scholar 

  7. Viola P, Jones M (2001) Rapid object detection using a boosted cascade of simple features. In: Conference on computer vision and pattern recognition

    Google Scholar 

  8. Nair VR, Charniya NN (2017) Drunk driving and drowsiness detection. In: International conference on intelligent computing and control (I2C2), Coimbatore, India, vol 2, pp 30–35

    Google Scholar 

  9. Kaehler A, Bradski G. Learning OpenCV3, Computer vision in C++ with OpenCV library

    Google Scholar 

  10. Dong W, Cheng CQ, Kai L, Bao-hua F (2011) The automatic control system of anti-drunk-driving. In: International conference on electronics, communication and control (ICECC), Ningbo, China. IEEE, pp 523–526

    Google Scholar 

  11. Wu Y-C, Xia Y-Q, Xie P, Ji X-W (2009) The design of an automotive anti-drunk driving system to guarantee the uniqueness of driver. In: International conference on information engineering and computer science (ICIECS), Wuhan, China. IEEE

    Google Scholar 

  12. Eun Jung Park (2008) Sensor report—MQ-3 Gas sensor. http://sensorworkshop.blogspot.in/2008/04/sensor-report-mq3-gas-sensor.html

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Acknowledgements

The authors would like to thank the anonymous reviewers for their valuable comments and suggestions. I (Vivek Nair—Author) would like to clarify that the participant (driver) is myself and give consent to be used in the study.

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Authors and Affiliations

  1. EXTC, V.E.S. Institute of Technology, Mumbai, India

    Vivek Nair & Nadir Charniya

Authors
  1. Vivek Nair
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  2. Nadir Charniya
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Corresponding author

Correspondence to Nadir Charniya .

Editor information

Editors and Affiliations

  1. SCAD Institute of Technology, Palladam, India

    Durai Pandian

  2. Department of Electrical and Computer Engineering, Ryerson University, Toronto, ON, Canada

    Xavier Fernando

  3. School of Computer and Security Science, Edith Cowan University, Joondalup, WA, Australia

    Zubair Baig

  4. Wenzhou Medical University, Wenzhou, China

    Fuqian Shi

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Nair, V., Charniya, N. (2019). Drunk Driving and Drowsiness Detection Alert System. In: Pandian, D., Fernando, X., Baig, Z., Shi, F. (eds) Proceedings of the International Conference on ISMAC in Computational Vision and Bio-Engineering 2018 (ISMAC-CVB). ISMAC 2018. Lecture Notes in Computational Vision and Biomechanics, vol 30. Springer, Cham. https://doi.org/10.1007/978-3-030-00665-5_113

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  • DOI: https://doi.org/10.1007/978-3-030-00665-5_113

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00664-8

  • Online ISBN: 978-3-030-00665-5

  • eBook Packages: EngineeringEngineering (R0)

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