Skip to main content
SpringerLink
Log in

IoT-Enabled Alcohol Detection System for Road Transportation Safety in Smart City

  • Conference paper
  • First Online:
Computational Science and Its Applications – ICCSA 2018 (ICCSA 2018)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10963))

Included in the following conference series:

Abstract

In this paper, an alcohol detection system was developed for road transportation safety in smart city using Internet of Things (IoT) technology. Two Blood Alcohol Content (BAC) thresholds are set and monitored with the use of a microcontroller. When the first threshold is reached, the developed system transmits the BAC level of the driver and the position coordinates of the vehicle to the central monitoring unit. At the reach of the second BAC threshold, the IoT-enabled alcohol detection system shuts down the vehicle’s engine, triggers an alarm and puts on the warning light indicator. A prototype of this scenario is designed and implemented such that a Direct Current (DC) motor acted as the vehicle’s engine while a push button served as its ignition system. The efficiency of this system is tested to ensure proper functionality. The deployment of this system will help in reducing the incidence of drunk driving-related road accidents in smart cities.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Killoran, A., et al.: Review of effectiveness of laws limiting blood alcohol concentration levels to reduce alcohol-related road injuries and deaths. Final report. Centre for Public Health Excellence (NICE), London (2010)

    Google Scholar 

  2. Lee, J.D., et al.: Assessing the feasibility of vehicle-based sensors to detect alcohol impairment. National Highway Traffic Safety Administration, Washington, DC (2010)

    Google Scholar 

  3. James, N., John, T.P.: Alcohol detection system. IJRCCT 3(1), 059–064 (2014)

    Google Scholar 

  4. Phani, S.A., et al.: Liquor detection through automatic motor locking system: in built (LDAMLS). Int. J. Comput. Eng. Res. (IJCER) 4(7), 2250–3005 (2014)

    Google Scholar 

  5. Federal Highway Administration. Highway Statistics 2014 - Policy (2014). https://www.fhwa.dot.gov/policyinformation/statistics/2014/

Download references

Acknowledgment

The authors wish to appreciate the Center for Research, Innovation, and Discovery (CU-CRID) of Covenant University, Ota, Nigeria, for partly funding this research.

Author information

Authors and Affiliations

  1. Department of Electrical and Information Engineering, Covenant University, Ota, Nigeria

    Stanley Uzairue, Victor O. Matthews & Segun I. Popoola

  2. Department of Electrical and Electronics Engineering, Federal University, Oye-Ekiti, Nigeria

    Joshua Ighalo

  3. Department of Electrical and Electronics Engineering, Petroleum Training Institute, Effurun, Warri, Nigeria

    Frances Nwukor

Authors
  1. Stanley Uzairue
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Joshua Ighalo
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Victor O. Matthews
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Frances Nwukor
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Segun I. Popoola
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Segun I. Popoola .

Editor information

Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Italy

    Beniamino Murgante

  3. Covenant University, Ota, Nigeria

    Sanjay Misra

  4. Saint Petersburg State University, Saint Petersburg, Russia

    Elena Stankova

  5. Polytechnic University of Bari, Bari, Italy

    Carmelo M. Torre

  6. University of Minho, Braga, Portugal

    Ana Maria A.C. Rocha

  7. Monash University, Clayton, Victoria, Australia

    David Taniar

  8. Kyushu Sangyo University, Fukuoka shi, Fukuoka, Japan

    Bernady O. Apduhan

  9. Politecnico di Bari, Bari, Italy

    Eufemia Tarantino

  10. Myongji University, Yongin, Korea (Republic of)

    Yeonseung Ryu

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG, part of Springer Nature

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Uzairue, S., Ighalo, J., Matthews, V.O., Nwukor, F., Popoola, S.I. (2018). IoT-Enabled Alcohol Detection System for Road Transportation Safety in Smart City. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2018. ICCSA 2018. Lecture Notes in Computer Science(), vol 10963. Springer, Cham. https://doi.org/10.1007/978-3-319-95171-3_55

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-95171-3_55

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-95170-6

  • Online ISBN: 978-3-319-95171-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation