Study on Mobile Passenger Support Systems for Public Transportation Using Multi-channel Data Dissemination

  • Koichi Goto
  • Yahiko Kambayashi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2362)


We have been developing mobile passenger support systems for the public transportation. In this application field, various kinds of data must be handled and integrated. Examples of such data are route information, fare information, area map, station map, planned operation schedule, real-time operation schedule, vehicle facilities and so on. Depending on the user situation, different information should be supplied and personalized. In this paper we propose the human support system used in the multi-channel data dissemination environments. On the other hand, the transportation systems can gather information about situations and demands of users and modify their services for users. In this paper we will discuss efficient methods to handle dynamic integration, personalization and filtering using multiple data dissemination channels and on-demand data channels. Current prototype system developed to be used visually handicapped passengers is also shown.


Central Server Public Transportation Mobile Terminal Disable Person Data Channel 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    D. Barbara, D.: Mobile Computing and Databases-A Survey. IEEE Transactions on Knowledge and Data Engineering, 11(1) January/February (1999) 108–117Google Scholar
  2. 2.
    Dunham, M., et al.: Mobile Computing and Databases: Anything New? SIGMOD Record, Special Section on Data Management Issues in Mobile Computing, 24(4): December (1995) 5–9Google Scholar
  3. 3.
    Imielinski, T. and Badrinath, B.: Mobile Wireless Computing-Challenge in Data Management. Communications of the ACM, 37(10) (1994) 18–28CrossRefGoogle Scholar
  4. 4.
    Ishida T., et al. Digital City Kyoto: Towards A Social Information Infrastructure. International Workshop on Cooperative Information Agents (CIA99), Cooperative Information Agents III, Lecture Note in Artificial Intelligence, Vol. 1652, (1999) 23–35Google Scholar
  5. 5.
    Imielinski, T., Viswanatham, S. and Badrinath, B.: Data on Air: Organization and Access. IEEE Transactions of Knowledge and Data Engineering, 9(3) May/June (1997) 353–372Google Scholar
  6. 6.
    Imielinski, T., Viswanathan, S. and Bardrinath., B.: Power Efficiency Filtering of Data on Air. Proceedings of the International Conference on Extending Database Technology (ETDB) (1994) 245–258Google Scholar
  7. 7.
    Hu, Q., Lee, D. and Lee., W.: Optimal Channel Allocation for Data Dissemination in Mobile Computing Environments. Proceedings of the 18th International Conference on Distributed Computing Systems (ICDCS98) (1998) 480–487Google Scholar
  8. 8.
    Goto, K., Matsubara, H. and Myojo, S.: A Mobile Guide System for Visually Disabled Persons. Proceedings of 4th International Symposium on Autonomous Decentralized Systems (ISADS99) (1999) 12–17Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Koichi Goto
    • 1
  • Yahiko Kambayashi
    • 2
  1. 1.School of InformaticsRailway Technical Research Institute and Kyoto UniversityTokyoJapan
  2. 2.School of InformaticsKyoto UniversityKyotoJapan

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