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Smart Bike Sharing System to Make the City Even Smarter

  • Monika RaniEmail author
  • O. P. Vyas
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 553)

Abstract

In the past few years, the growing population in the smart city demands an efficient transportation sharing (bike sharing) system for its development. The bike sharing as we know is affordable, easily accessible and reliable mode of transportation. But an efficient bike sharing system should be capable not only of sharing bike but also of providing information regarding the availability of bike per station, route business, time/daywise bike schedule. The embedded sensors are able to opportunistically communicate through wireless communication with stations when available, providing real-time data about tours/minutes, speed, effort, rhythm, etc. Based on our study analysis data to predict regarding the bike’s available at stations, bike schedule, a location of the nearest hub where a bike is available, etc., reduces the user time and effort.

Keywords

Smart cities Bike sharing NS2 simulator 

References

  1. 1.
    Naphade, M., Banavar, G., Harrison, C., Paraszczak, J., & Morris, R.: Smarter cities and their innovation challenges. Computer, 44(6), pp. 32–39 (2011).Google Scholar
  2. 2.
    Rietveld, P., & Daniel, V.: Determinants of bicycle use: do municipal policies matter?. Transportation Research Part A: Policy and Practice, 38(7), pp. 531–550 (2004).Google Scholar
  3. 3.
    Geels, F., & Raven, R.: Non-linearity and expectations in niche-development trajectories: ups and downs in Dutch biogas development (1973–2003). Technology Analysis & Strategic Management, 18(3–4), pp. 375–392 (2006).Google Scholar
  4. 4.
    DeMaio, P.: Bike-sharing: History, impacts, models of provision, and future. Journal of Public Transportation, 12(4), 3 (2009).Google Scholar
  5. 5.
    Quiguer, S.: Acceptabilité, acceptation et appropriation des Systèmes de Transport Intelligents: élaboration d’un canevas de co-conception multidimensionnelle orientée par l’activité (Doctoral dissertation, Université Rennes 2) (2013).Google Scholar
  6. 6.
    Melaina, M., & Bremson, J.: Refueling availability for alternative fuel vehicle markets: sufficient urban station coverage. Energy Policy, 36(8), pp. 3233–3241 (2008).Google Scholar
  7. 7.
    Ballet, J. C., & Clavel, R.: Le covoiturage en France et en Europe: état des lieux et perspectives (2007).Google Scholar
  8. 8.
    Pucher, J., & Buehler, R.: Why Canadians cycle more than Americans: a comparative analysis of bicycling trends and policies. Transport Policy, 13(3), pp. 265–279 (2006).Google Scholar
  9. 9.
    Clavel, R., Legrand, P., & LOXANE, P.: Le covoiturage dynamique: étude préalable avant expérimentation (2009).Google Scholar
  10. 10.
    Perkins, C., Belding-Royer, E., & Das, S.: Ad hoc on-demand distance vector (AODV) routing (No. RFC 3561) (2003).Google Scholar
  11. 11.
    DeMaio, P.: Bike-sharing: History, impacts, models of provision, and future. Journal of Public Transportation, 12(4), 3 (2009).Google Scholar
  12. 12.
    Rani, M., Nayak, R., & Vyas, O. P.: An ontology-based adaptive personalized e-learning system, assisted by software agents on cloud storage. Knowledge-Based Systems, 90, pp. 33–48 (2015).Google Scholar
  13. 13.
    Rani, M., Srivastava, K. V., & Vyas, O. P.: An ontological learning management system. Computer Applications in Engineering Education (2016).Google Scholar
  14. 14.
    Blanke, J. E. N. N. I. F. E. R., Chiesa, T. H. E. A., & Herrera, E. T.: The travel & tourism competitiveness index 2009: Measuring sectoral drivers in a downturn. The Travel & Tourism Competitiveness Report 2009: Managing in a Time of Turbulence, pp. 3–37 (2009).Google Scholar
  15. 15.
    Hoffmann, C.: Erfolgsfaktoren umweltgerechter Mobilitätsdienstleistungen: Einflussfaktoren auf Kundenbindung am Beispiel DB Carsharing und Call a Bike. Osnabrück (2010).Google Scholar
  16. 16.
    Cervero, R., & Duncan, M.: Walking, bicycling, and urban landscapes: evidence from the San Francisco Bay Area. American journal of public health, 93(9), pp. 1478–1483 (2003).Google Scholar
  17. 17.
    Maurer, L. K.: Feasibility study for a bicycle sharing program in Sacramento, California. In Transportation Research Board 91st Annual Meeting (No. 12–4431) (2012).Google Scholar
  18. 18.
  19. 19.
  20. 20.
  21. 21.
    D. Terr. “Weighted Mean.” From MathWorld-A Wolfram Web Resource, created by Eric W. Weisstein. http://mathworld.wolfram.com/WeightedMean.html 58, pp. 13918–13927 (2004).
  22. 22.
    Perkins, C., Belding-Royer, E., & Das, S.: Ad hoc on-demand distance vector (AODV) routing (No. RFC 3561) (2003).Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2017

Authors and Affiliations

  1. 1.Department of Information TechnologyIndian Institute of Information TechnologyAllahabadIndia

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