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International Wireless Internet Conference

WICON 2014: Wireless Internet pp 135–140Cite as

Intelligent and Efficient Car Management Application for Advanced Green Routing

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Abstract

The tremendous growth of the transportation systems during the last decades has created a significant environmental impact. As a result, in order to reduce the atmospheric pollution many attempts have been employed, including eco-driving systems. However, the scope of such systems is only to attempt to inform the user about his driving behaviour. In the current paper, a novel system targeted for supporting green daily commuting habits, with a particular focus on helping the user save on fuel expenses and time on a regular daily basis is proposed and its functional architecture is fully presented.

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Notes

  1. 1.

    The term eco-driving is used to describe energy efficient use of vehicles.

References

  1. United States Climate Action Report 2014 (2014), www.state.gov

  2. Jovanovic, A., Pamucar, D., Pejcic-Tarle, S.: Green vehicle routing in urban zones - a neuro-fuzzy approach. Expert Syst. Appl. 41(7), 3189–3203 (2014)

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  3. Sadek, A., Basha, N.: Self-learning intelligent agents for dynamic traffic routing on transportation networks. In: Minai, A., Braha, D., Bar-Yam, Y. (eds.) Unifying Themes in Complex Systems, pp. 503–510. Springer, Heidelberg (2008)

    Google Scholar 

  4. Scania Driver active prediction. http://www.scania.com/products-services/trucks/safety-driver-support/driver-support-systems/active-prediction/

  5. HONDA Ecological Drive Assist System. http://world.honda.com/news/2008/4081120Ecological-Drive-Assist-System/

  6. Greenroad website. http://greenroad.com

  7. Greenmeter application. http://hunter.pairsite.com/greenmeter/

  8. Archimate 2.1 Specification. http://www.archimate.nl

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Acknowledgement

This work has been performed under the Greek National project CARMA (11\(\Sigma \Upsilon \)N_10_877), which has received research funding from the Operational Programme “Competitiveness & Entrepreneurship” of the National Strategic Reference Framework NSRF 2007–2013. This paper reflects only the authors’ views, and the Operational Programme in not liable for any use that may be made of the information contained therein.

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Authors and Affiliations

  1. National Technical University of Athens, Athens, Greece

    Ioannis Loumiotis, V. Asthenopoulos, Evgenia Adamopoulou, Konstantinos Demestichas & E. Sykas

Authors
  1. Ioannis Loumiotis
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  2. V. Asthenopoulos
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  3. Evgenia Adamopoulou
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  4. Konstantinos Demestichas
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  5. E. Sykas
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Corresponding author

Correspondence to Ioannis Loumiotis .

Editor information

Editors and Affiliations

  1. University of Santiago, Aveiro, Portugal

    Shahid Mumtaz

  2. Institute of Telecommunication, Aveiro, Portugal

    Jonathan Rodriguez

  3. Finland Technical, University of Oulu, Oulu, Finland

    Marcos Katz

  4. InterDigital Communications, King of Prussia, Pennsylvania, USA

    Chonggang Wang

  5. Departamento de Matemática e Engenharias, University of Madeira, Funchal, Portugal

    Alberto Nascimento

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© 2015 Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Cite this paper

Loumiotis, I., Asthenopoulos, V., Adamopoulou, E., Demestichas, K., Sykas, E. (2015). Intelligent and Efficient Car Management Application for Advanced Green Routing. In: Mumtaz, S., Rodriguez, J., Katz, M., Wang, C., Nascimento, A. (eds) Wireless Internet. WICON 2014. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 146. Springer, Cham. https://doi.org/10.1007/978-3-319-18802-7_19

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  • DOI: https://doi.org/10.1007/978-3-319-18802-7_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-18801-0

  • Online ISBN: 978-3-319-18802-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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