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Participatory Sensing for Improving Urban Mobility

  • Miguel Angel Ylizaliturri-Salcedo
  • Saul Delgadillo-Rodriguez
  • J. Antonio Garcia-Macias
  • Monica Tentori
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8276)

Abstract

Urban computing leverages mobile participatory and opportunistic sensing to monitor and provide continuous awareness of urban cities. CICESE Research Center offers students and staff an intra-campus transportation service called CICEMóvil to help them get around campus. However this service lacks of formality as trips are constantly being cancelled without previous notification and it’s hard to discover when the vehicle is going to be available for the next trip. We present the design and development of a mobile augmented reality system using participatory and opportunistic sensing to empower users to track and share the location and status of CICEMóvil via their smartphones. We concluded discussing directions for future work, as we aim to study how participatory sensing could be used to promote self-reflection at a collective level through the design and evaluation of mobile sensing campaigns in public transportation.

Keywords

urban sensing participatory sensing smartphones supervision transportation mobile applications 

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References

  1. 1.
    Burke, J.A., Estrin, D., Hansen, M., Parker, A., Ramanathan, N., Reddy, S., Srivastava, M.B.: Participatory sensing (May 2006)Google Scholar
  2. 2.
    Cuff, D., Hansen, M., Kang, J.: Urban sensing. Communications of the ACM 51(3), 24–33 (2008)CrossRefGoogle Scholar
  3. 3.
    Calabrese, F., Colonna, M., Lovisolo, P., Parata, D., Ratti, C.: Real-Time Urban Monitoring Using Cell Phones: A Case Study in Rome. IEEE Transactions on Intelligent Transportation System 12(1), 141–151 (2011)CrossRefGoogle Scholar
  4. 4.
    Zhou, P., Zheng, Y., Li, M.: How long to wait? In: Proceedings of the 10th International Conference on Mobile Systems, Applications, and Services, MobiSys 2012, p. 379 (2012)Google Scholar
  5. 5.
    Mohan, P., Padmanabhan, V.N., Ramjee, R.: Nericell. In: Proceedings of the 6th ACM Conference on Embedded Network Sensor Systems, SenSys 2008, p. 323 (2008)Google Scholar
  6. 6.
    Bhoraskar, R., Vankadhara, N., Raman, B., Kulkarni, P.: Wolverine: Traffic and road condition estimation using smartphone sensors. In: 2012 Fourth International Conference on Communication Systems and Networks (COMSNETS 2012), pp. 1–6 (January 2012)Google Scholar
  7. 7.
    Yoon, J., Noble, B., Liu, M.: Surface street traffic estimation. In: Proceedings of the 5th International Conference on Mobile Systems, Applications and Services, MobiSys 2007, p. 220 (2007)Google Scholar
  8. 8.
    Zheng, Y., Liu, Y., Yuan, J., Xie, X.: Urban computing with taxicabs. In: Proceedings of the 13th International Conference on Ubiquitous Computing, UbiComp 2011, p. 89 (2011)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Miguel Angel Ylizaliturri-Salcedo
    • 1
  • Saul Delgadillo-Rodriguez
    • 1
  • J. Antonio Garcia-Macias
    • 1
  • Monica Tentori
    • 1
  1. 1.Departamento de Ciencias de la ComputaciónCentro de Investigación Científica y de Educación Superior de EnsenadaEnsenadaMéxico

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