Complex Mobile User Adaptive System Framework for Mobile Wireless Devices

  • Ondrej Krejcar
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 45)

Abstract

Paper describes a concept of User Adaptive System (UAS) as well as Predictive Data Push Technology (PDPT) Framework and Biotelemetrical Monitoring System (BMS) as two joined parts of complex UAS framework. Main focus is in contribution of UAS to user or patient and his life quality. A Position Oriented Database on a server and mobile devices is described as important part of whole UAS, because the position and context of user are one of the most important areas of UAS. Also the problem of low data throughput on mobile devices is described, which can be solved by PDPT framework. Localization and user tracking is described only as a necessary condition for prebuffering realization because the PDPT Core makes a decision when and which artifact (large data files) need to be prebuffered. Every artifact is stored along with its position information (e.g. in building or larger area environment). The accessing of prebuffered data artifacts on mobile device improve the download speed and response time needed to view large multimedia data. The conditions for real stocking in corporate areas are discussed at the end of paper along with problems that must be solved before stocking.

Keywords

User Adaptive System Mobile Device Localization Biotelemetry Position Oriented Database Prebuffering 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Poslad, S.: Ubiquitous Computing: Smart Devices, Environments and Interactions. John Wiley & Sons, Ltd., London (2009), ISBN 978-0-470-03560-3 CrossRefGoogle Scholar
  2. 2.
    Lewis, D., O’Sullivan, D.: Adaptive Systems for Ubiquitous Computing. In: Proceedings of the 1st international symposium on Information and communication technologies. ACM International Conference Proceeding Series, vol. 49, p. 156 (2003)Google Scholar
  3. 3.
    Satyanarayanan, M.: Pervasive computing: vision and challenges. IEEE Personal Communications 8, 10–17 (2001)CrossRefGoogle Scholar
  4. 4.
    Coen, M.H.: Design principles for Inteligent environments. In: Proceedings of 15th National/10th Conference on Artificial Intelligence/Innovative Applications of Artificial Intelligence, pp. 547–554 (1998)Google Scholar
  5. 5.
    Cook, D.J., Das, S.K.: How smart are our environments? An updated look at the state of the art. Pervasive and Mobile Computing 3(2), 53–73 (2007)CrossRefGoogle Scholar
  6. 6.
    Brida, P., Duha, J., Krasnovsky, M.: On the accuracy of weighted proximity based localization in wireless sensor networks. In: Personal Wireless Communications. IFIP, vol. 245, pp. 423–432 (2007)Google Scholar
  7. 7.
    Krejcar, O.: Prebuffering as a way to exceed the data transfer speed limits in mobile control systems. In: ICINCO 2008, 5th International Conference on Informatics in Control, Automation and Robotics, Funchal, Portugal, May 11-15, pp. 111–114 (2008)Google Scholar
  8. 8.
    Krejcar, O., Cernohorsky, J.: New Possibilities of Intelligent Crisis Management by Large Multimedia Artifacts Prebuffering. In: I.T. Revolutions 2008, Venice, Italy, December 17- 19. LNICST, vol. 11, pp. 44–59. Springer, Heidelberg (2008)Google Scholar
  9. 9.
    Krejcar, O.: Problem Solving of Low Data Throughput on Mobile Devices by Artefacts Prebuffering. EURASIP Journal on Wireless Communications and Networking, Article ID 802523, 8 pages (2010)Google Scholar
  10. 10.
    Nielsen, J.: Usability Engineering. Morgan Kaufmann, San Francisco (1994)MATHGoogle Scholar
  11. 11.
    Haklay, M., Zafiri, A.: Usability engineering for GIS: learning from a screenshot. The Cartographic Journal 45(2), 87–97 (2008)CrossRefGoogle Scholar
  12. 12.
    Ramrekha, T.A., Politis, C.: An Adaptive QoS Routing Solution for MANET Based Multimedia Communications in Emergency Cases. In: MOBILIGHT 2009, Athens, Greece. LNICST, vol. 13, pp. 74–84. Springer, Heidelberg (2009)Google Scholar
  13. 13.
    Krejcar, O., Janckulik, D., Motalova, L., Kufel, J.: Mobile Monitoring Stations and Web Visualization of Biotelemetric System - Guardian II. In: Mehmood, R., et al. (eds.) EuropeComm 2009. LNICST, vol. 16, pp. 284–291. Springer, Heidelberg (2009)Google Scholar
  14. 14.
    Cerny, M., Penhaker, M.: Biotelemetry. In: 14th Nordic-Baltic Conference an Biomedical Engineering and Medical Physics, Riga, Latvia, June 16-20. IFMBE Proceedings, vol. 20, pp. 405–408 (2008)Google Scholar
  15. 15.
    Krejcar, O.: Full Scale Software Support on Mobile Lightweight Devices by Utilization of all Types of Wireless Technologies. In: Granelli, F., Skianis, C., Chatzimisios, P., Xiao, Y., Redana, S. (eds.) Mobilight 2009. LNICST, vol. 13, pp. 173–184. Springer, Heidelberg (2009)Google Scholar
  16. 16.
    Penhaker, M., Cerny, M., Martinak, L., Spisak, J., Valkova, A.: HomeCare - Smart embedded biotelemetry system. In: World Congress on Medical Physics and Biomedical Engineering, Seoul, South Korea, August 27-September 01. PTS 1-6, vol. 14, pp. 711–714 (2006)Google Scholar
  17. 17.
    Brasche, G.P., Fesl, R., Manousek, W., Salmre, I.W.: Location-based caching for mobile devices. United States Patent, Microsoft Corporation, Redmond, WA, US, 20070219708 (2007)Google Scholar
  18. 18.
    Squibbs, R.F.: Cache management in a mobile device. United States Patent, Hewlett-Packard Development Company, L.P., 20040030832 (2004)Google Scholar

Copyright information

© ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering 2010

Authors and Affiliations

  • Ondrej Krejcar
    • 1
  1. 1.Department of measurement and controlVSB Technical University of Ostrava, Center for Applied CyberneticsOstrava PorubaCzech Republic

Personalised recommendations