Skip to main content
SpringerLink
Log in

A Fuzzy-Based System for Safe Driving Information in VANETs

  • Conference paper
  • First Online:
Book cover Advances on Broadband and Wireless Computing, Communication and Applications (BWCCA 2018)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 25))

Abstract

Ambient intelligence (AmI) deals with a new world of ubiquitous computing devices, where physical environments interact intelligently and unobtrusively with people. AmI environments can be diverse, such as homes, offices, meeting rooms, schools, hospitals, control centers, vehicles, tourist attractions, stores, sports facilities, and music devices. In this paper, we propose a Fuzzy-based system for safe driving information in VANETs. The proposed system considers in-car environment data and driver’s vital signs data to make the decision. Then uses the smart-box to inform the driver and change his mood. We want to realize a new system to support the driver for save driving. We evaluated the performance of proposed system by computer simulations. From the simulations results, we conclude that the driver vital information, vehicle mobility information and car environment information have different effects to the driver.

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 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
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. Lindwer, M., Marculescu, D., Basten, T., Zimmermann, R., Marculescu, R., Jung, S., Cantatore, E.: Ambient intelligence visions and achievements: linking abstract ideas to real-world concepts. In: Design, Automation and Test in Europe Conference and Exhibition, pp. 10–15 (2003)

    Google Scholar 

  2. Acampora, G., Cook, D., Rashidi, P., Vasilakos, A.V.: A survey on ambient intelligence in health care. Proc. IEEE 101(12), 2470–2494 (2013)

    Article  Google Scholar 

  3. Aarts, E., Wichert, R.: Ambient intelligence. In: Technology Guide, pp. 244–249 (2009)

    Chapter  Google Scholar 

  4. Aarts, E., de Ruyter, B.: New research perspectives on ambient intelligence. J. Ambient Intell. Smart Environ. 1(1), 5–14 (2009)

    Google Scholar 

  5. Vasilakos, A., Pedrycz, W.: Ambient Intelligence, Wireless Networking, And Ubiquitous Computing. Norwood. Artech House Inc., Norwood (2006)

    Google Scholar 

  6. Sadri, F.: Ambient intelligence: a survey. ACM Comput. Surv. 43(4), 66 (2011). Article 36

    Article  Google Scholar 

  7. Santi, P.: Mobility Models for Next Generation Wireless Networks: Ad Hoc, Vehicular and Mesh Networks. Wiley, Chichester (2012)

    Book  Google Scholar 

  8. Hartenstein, H., Laberteaux, L.: A tutorial survey on vehicular ad hoc networks. IEEE Commun. Mag. 46(6), 164–171 (2008)

    Article  Google Scholar 

  9. Karagiannis, G., Altintas, O., Ekici, E., Heijenk, G., Jarupan, B., Lin, K., Weil, T.: Vehicular networking: a survey and tutorial on requirements, architectures, challenges, standards and solutions. IEEE Commun. Surv. Tutor. 13(4), 584–616 (2011)

    Article  Google Scholar 

  10. Calhan, A.: A fuzzy logic based clustering strategy for improving vehicular ad-hoc network performance. Sadhana 40(2), 351–367 (2015)

    Article  Google Scholar 

  11. Kandel, A.: Fuzzy Expert Systems. CRC Press, Boca Raton (1992)

    Google Scholar 

  12. Zimmermann, H.J.: Fuzzy Set Theory and Its Applications, Second Revised Edition. Kluwer Academic Publishers, The Netherlands (1991)

    Book  Google Scholar 

  13. McNeill, F.M., Thro, E.: Fuzzy Logic, A Practical Approach. Academic Press Inc., The Netherlands (1994)

    MATH  Google Scholar 

  14. Zadeh, L.A., Kacprzyk, J.: Fuzzy Logic For The Management of Uncertainty. Wiley, Chichester (1992)

    Google Scholar 

  15. Procyk, T.J., Mamdani, E.H.: A Linguistic Self-organizing Process Controller. Automatica 15(1), 15–30 (1979)

    Article  Google Scholar 

  16. Klir, G.J., Folger, T.A.: Fuzzy Sets, Uncertainty and Information. Prentice Hall, Englewood Cliffs (1988)

    MATH  Google Scholar 

  17. Munakata, T., Jani, Y.: Fuzzy Systems: An Overview. Commun ACM 37(3), 69–76 (1994)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Graduate School of Engineering, Fukuoka Institute of Technology (FIT), 3-30-1 Wajiro -Higashi, Higashi -Ku, Fukuoka, 811-0295, Japan

    Kevin Bylykbashi, Yi Liu & Kosuke Ozera

  2. Department of Information and Communication Engineering, Fukuoka Institute of Technology (FIT), 3-30-1 Wajiro -Higashi, Higashi -Ku, Fukuoka, 811-0295, Japan

    Leonard Barolli

  3. Department of Advanced Sciences, Faculty of Science and Engineering, Hosei University, 3-7-2, Kajino-machi, Koganei-shi, Tokyo, 184-8584, Japan

    Makoto Takizawa

Authors
  1. Kevin Bylykbashi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yi Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Kosuke Ozera
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Leonard Barolli
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Makoto Takizawa
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kevin Bylykbashi .

Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, Faculty of Information Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

  2. Tunghai University, Taichung, Taiwan

    Fang-Yie Leu

  3. Rissho University, Tokyo, Japan

    Tomoya Enokido

  4. Asia University, Taichung, Taiwan

    Hsing-Chung Chen

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Bylykbashi, K., Liu, Y., Ozera, K., Barolli, L., Takizawa, M. (2019). A Fuzzy-Based System for Safe Driving Information in VANETs. In: Barolli, L., Leu, FY., Enokido, T., Chen, HC. (eds) Advances on Broadband and Wireless Computing, Communication and Applications. BWCCA 2018. Lecture Notes on Data Engineering and Communications Technologies, vol 25. Springer, Cham. https://doi.org/10.1007/978-3-030-02613-4_58

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-02613-4_58

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-02612-7

  • Online ISBN: 978-3-030-02613-4

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation