Generic Personal Assistance Architecture for Mobile Environments

  • Gerald Bieber
Part of the Studies in Computational Intelligence book series (SCI, volume 93)


The computing power of mobile computers is comparable to the PCs of some years ago. In addition, PDAs or mobile phones are equipped with a high connectivity and provide a multimodal interface by a high resolution display, vibration feedback and sound functionality. This feature enables the use of mobile phones as personal information manager and personal assistance for business and the everyday life. The progress of personal assistance is supported by the inclusion of external environment information and user related data. By using new interfaces and sensors, an additional and comprehensive understanding of the user’s situation can be determined. Hereby a planning of the user’s task is supported and a scheduling of the user’s activities will be available. This chapter shows an improving approach of the generic architecture for mobile personal situation aware assistance and describes the modules by sample applications and gives an outlook on upcoming challenges of research in activity and assistance models.


Mobile Phone Task Execution Task Model Mobile Environment Execution Plan 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Chavez E., Kirste T., Mobile visitor information system, CG topics 3/99, Darmstadt, Germany, ISSN 0936-2770, 1999Google Scholar
  2. 2.
    Want R., Hopper A., Falcão V., Gibbons J., The active badge location system, Olivetti Research Ltd. (ORL)/Xerox PARC research laboratories, ACM Transactions on Information Systems, 10:91–102, Jan. 1992CrossRefGoogle Scholar
  3. 3.
    Rhodes B., Using physical context for just-in-time information retrieval, IEEE Transactions on Computers, 52(8):1011–1014, Aug. 2003CrossRefGoogle Scholar
  4. 4.
    Chávez E., Ide R., Kirste T., Interactive applications of personal situation-aware assistants. Computers & Graphics, 23(6):903–915, 1999CrossRefGoogle Scholar
  5. 5.
    Satoh I., Location-Based Services in Ubiquitous Computing Environments, Lecture Notes in Computer Science, vol. 2910, Springer, Berlin, Germany, 2003Google Scholar
  6. 6.
    Paternò F., Mancini C., Meniconi S., ConcurTaskTrees: A diagrammatic notation for specifying task models. In Proc. of IFIP Int. Conf. on Human-Computer Interaction Interact ’97 (Sydney, July 1997). Chapman & Hall, London, 1997, pp. 362–369Google Scholar
  7. 7.
    Bieber G., Tominski C., Visualization techniques for personal tasks on mobile computers, In Proceedings of the HCII2003, vol. 3, Lawrence Erlbaum, Crete, Greece, 2003, ISBN 0-8058-4932-7Google Scholar
  8. 8.
    Schilit W.N., A system architecture for context-aware mobile computing, Ph.D. Thesis, Columbia University, New York, 1995Google Scholar
  9. 9.
    Bieber G., The approach of a personal task model for mobile computing, In MOST International Conference 2002, Warsaw, Poland, ISBN 83-87091-32-4Google Scholar
  10. 10.
    Garlan D., Schmerl B., The RADAR Architecture for personal cognitive assistance, International Journal of Software Engineering and Knowledge Engineering, 17(2), Apr. 2007Google Scholar
  11. 11.
    Mcgraw K., Herbison-Briggs K., Knowledge Acquisition, Principles and Guidelines, International Editions, Prentice Hall, London, 1989Google Scholar
  12. 12.
    Pereira J., Englmeier K., Rojas C., A model for personal assistance in complex information spaces, In Proceedings of the American Society for Information Science and Technology, vol. 39(1), 2005Google Scholar
  13. 13.
    Voinikonis A., Irmscher K., Schulze H., Distributed processing of reminding tasks within the mobile memory aid system, MEMOS, Personal and Ubiquitous Computing, Springer, London, DOI 10.1007/s00779-004-0332-5, 2005Google Scholar
  14. 14.
    ISTAG, Involving users in the Development of Ambient Intelligence, ISTAG Report on Experience and Application Research, 2004Google Scholar
  15. 15.
    Heider T., Kirste T., Architecture considerations for interoperable multi-modal assistant systems, In Proc. DSV-IS 2002, Rostock, Germany, 2002Google Scholar
  16. 16.
    Hildebrand A., Sa V., EMBASSI: Electronic Multimedia and Service Assistance, In Proc. IMC 2000, Rostock, Germany, 2000Google Scholar
  17. 17.
    Iqbal S.T., MeWS-IT: A mental workload based system for interruption timing. In Proceedings of the ACM Symposium on User Interface Software and Technology, Doctoral Symposium, Seattle, WA, Oct. 2005Google Scholar
  18. 18.
    Chen G., Kotz D., A survey of context-aware mobile computing research, Dartmouth Computer Science Technical Report TR2000-381, 2000Google Scholar
  19. 19.
    Giersich M., Bieber G., Personal mobile navigational systems – design considerations and experiences, Computer & Graphics, 25(4):563–570, Elsevier Science, UK, 2001, ISSN 0097-8493CrossRefGoogle Scholar
  20. 20.
    Kirste T., Rieck A., A mobile network administration system: Conception and realization. In Proc. AKIDA’98, Aachen, Germany, June 3–4, 1998Google Scholar
  21. 21.
    Oppermann R., Specht M., A context-sensitive nomadic exhibition guide, In Handheld and Ubiquitous Computing (Proc. 2nd Int. Symp., Bristol, UK, Sep. 2000), P. Thomas and H.W. Gellersen (eds.), Springer, Berlin, pp. 127–142, 2000CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Gerald Bieber
    • 1
  1. 1.Fraunhofer-Institute for Computer GraphicsRostockGermany

Personalised recommendations