Bringing Quality of Context into Wearable Human Activity Recognition Systems

  • Claudia Villalonga
  • Daniel Roggen
  • Clemens Lombriser
  • Piero Zappi
  • Gerhard Tröster
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5786)

Abstract

Quality of Context (QoC) in context-aware computing improves reasoning and decision making. Activity recognition in wearable computing enables context-aware assistance. Wearable systems must include QoC to participate in context processing frameworks common in large ambient intelligence environments. However, QoC is not specifically defined in that domain. QoC models allowing activity recognition system reconfiguration to achieve a desired context quality are also missing. Here we identify the recognized dimensions of QoC and the performance metrics in activity recognition systems. We discuss how the latter maps on the former and provide provide guidelines to include QoC in activity recognition systems. On the basis of gesture recognition in a car manufacturing case study, we illustrate the signification of QoC and we present modeling abstractions to reconfigure an activity recognition system to achieve a desired QoC.

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References

  1. 1.
    Dey, A.K., Abowd, G.D., Salber, D.: A conceptual framework and a toolkit for supporting the rapid prototyping of context-aware applications. Human-Computer Interaction 16(2), 97–166 (2001)CrossRefGoogle Scholar
  2. 2.
    Stiefmeier, T., Roggen, D., Ogris, G., Lukowicz, P., Tröster, G.: Wearable activity tracking in car manufacturing. IEEE Pervasive Computing 7(2), 42–50 (2008)CrossRefGoogle Scholar
  3. 3.
    Tentori, M., Favela, J.: Activity-aware computing for healthcare. IEEE Pervasive Computing 7(2), 51–57 (2008)CrossRefGoogle Scholar
  4. 4.
    Consolvo, S., Roessler, P., Shelton, B., LaMarca, A., Schilit, B., Bly, S.: Technology for care networks of elders. IEEE Pervasive Computing 3(2), 22–29 (2004)CrossRefGoogle Scholar
  5. 5.
    Bardram, J.E.: Applications of context-aware computing in hospital work: examples and design principles. In: Proc. ACM Symposium on Applied Computing (SAC), pp. 1574–1579 (2004)Google Scholar
  6. 6.
    Fleck, M., Frid, M., Kindberg, T., O’Brien-Strain, E., Rajani, R., Spasojevic, M.: From informing to remembering: Ubiquitous systems in interactive museums. IEEE Pervasive Computing 1(2), 13–21 (2002)CrossRefGoogle Scholar
  7. 7.
    Schilit, B.N., Adams, N., Want, R.: Context-aware computing applications. In: Proc. IEEE Workshop on Mobile Computing Systems and Applications, pp. 85–90 (1994)Google Scholar
  8. 8.
    Böhm, S., Koolwaaij, J., Luther, M., Souville, B., Wagner, M., Wibbels, M.: Introducing IYOUIT. In: Proc. Int’l Semantic Web Conference, pp. 804–817 (2008)Google Scholar
  9. 9.
    Henricksen, K., Indulska, J.: Modelling and using imperfect context information. In: Proc. 2nd IEEE Conf. Pervasive Computing and Communications Workshops, pp. 33–37 (2004)Google Scholar
  10. 10.
    Buchholz, T., Kuepper, A., Schiffers, M.: Quality of context: What it is and why we need it. In: Proc. Workshop of the HP OpenView University Association, HPOVUA (2003)Google Scholar
  11. 11.
  12. 12.
    Berchtold, M., Decker, C., Riedel, T., Zimmer, T., Beigl, M.: Using a context quality measure for improving smart appliances. In: Proc. 27th Int’l Conf. Distributed Computing Systems Workshops (ICDCSW), p. 52 (2007)Google Scholar
  13. 13.
    Lei, H., Sow, D.M., John, S., Davis, I., Banavar, G., Ebling, M.R.: The design and applications of a context service. ACM SIGMOBILE Mobile Computing Communications Review 6(4), 45–55 (2002)CrossRefGoogle Scholar
  14. 14.
    Judd, G., Steenkiste, P.: Providing contextual information to pervasive computing applications. In: Proc. 1st IEEE Int’l Conf. on Pervasive Computing and Communications (PERCOM), p. 133 (2003)Google Scholar
  15. 15.
    Gu, T., Wang, X., Pung, H., Zhang, D.: An ontology-based context model in intelligent environments. In: Proceedings of Communication Networks and Distributed Systems Modeling and Simulation Conference, CNDS 2004 (2004)Google Scholar
  16. 16.
    Zimmer, T.: Qoc: Quality of context - improving the performance of context-aware applications. In: Advances in Pervasive Computing. Adj. Proc. Pervasive., vol. 207, pp. 209–214 (2006)Google Scholar
  17. 17.
    Sheikh, K., Wegdam, M., van Sinderen, M.: Middleware support for quality of context in pervasive context-aware systems. In: Proc. 5th IEEE Int’l Conf. on Pervasive Computing and Communications Workshops (PERCOMW), pp. 461–466 (2007)Google Scholar
  18. 18.
    Manzoor, A., Truong, H.L., Dustdar, S.: On the evaluation of quality of context. In: Roggen, D., Lombriser, C., Tröster, G., Kortuem, G., Havinga, P. (eds.) EuroSSC 2008. LNCS, vol. 5279, pp. 140–153. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  19. 19.
    Bu, Y., Gu, T., Tao, X., Li, J., Chen, S., Lu, J.: Managing quality of context in pervasive computing. In: Proc. 6th Int’l Conf. on Quality Software (QSIC), pp. 193–200 (2006)Google Scholar
  20. 20.
    Krause, M., Hochstatter, I.: Challenges in modelling and using quality of context (qoc). In: Magedanz, T., Karmouch, A., Pierre, S., Venieris, I.S. (eds.) MATA 2005. LNCS, vol. 3744, pp. 324–333. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  21. 21.
    Kim, Y., Lee, K.: A quality measurement method of context information in ubiquitous environments. In: Proc. Int’l Conf. on Hybrid Information Technology (ICHIT), vol. 2, pp. 576–581 (2006)Google Scholar
  22. 22.
    Strang, T., Linnhoff-Popien, C., Frank, K.: Cool: A context ontology language to enable contextual interoperability. In: Proc. 4th IFIP WG6.1 Int’l Conf. on Distributed Applications and Interoperable Systems (DAIS), pp. 236–247 (2003)Google Scholar
  23. 23.
    Heinz, E., Kunze, K., Gruber, M., Bannach, D., Lukowicz, P.: Using wearable sensors for real-time recognition tasks in games of martial arts – an initial experiment. Proc. IEEE Symposium on Computational Intelligence and Games, CIG (2006)Google Scholar
  24. 24.
    Kallio, S., Kela, J., Korpipää, P., Mäntyjärvi, J.: User independent gesture interaction for small handheld devices. Int’l J. of Pattern Recognition and Artificial Intelligence 20(4), 505–524 (2006)CrossRefGoogle Scholar
  25. 25.
    Bächlin, M., Roggen, D., Plotnik, M., Hausdorff, J.M., Tröster, G.: Online detection of freezing of gait in parkinson’s disease patients: A performance characterization. In: Accepted for Proc. 4th Int’l Conf. on Body Area Networks (2009)Google Scholar
  26. 26.
    Stäger, M., Lukowicz, P., Tröster, G.: Power and accuracy trade-offs in sound-based context recognition systems. Pervasive and Mobile Computing 3, 300–327 (2007)CrossRefGoogle Scholar
  27. 27.
    Bharatula, N., Lukowicz, P., Tröster, G.: Functionality-power-packaging considerations in context aware wearable systems. Personal and Ubiquitous Computing 12(2), 123–141 (2008)CrossRefGoogle Scholar
  28. 28.
    Van Laerhoven, K., Gellersen, H.W.: Spine versus porcupine: a study in distributed wearable activity recognition. In: Proc. 8th Int’l Symposium on Wearable Computers (ISWC), pp. 142–149 (2004)Google Scholar
  29. 29.
    Bao, L., Intille, S.S.: Activity recognition from user-annotated acceleration data. In: Ferscha, A., Mattern, F. (eds.) PERVASIVE 2004. LNCS, vol. 3001, pp. 1–17. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  30. 30.
    Ward, J., Lukowicz, P., Tröster, G., Starner, T.: Activity recognition of assembly tasks using body-worn microphones and accelerometers. IEEE Trans. Pattern Analysis and Machine Intelligence 28(10), 1553–1567 (2006)CrossRefGoogle Scholar
  31. 31.
    Reilly, D., Siewiorek, D., Smailagic, A.: Power consumption and performance analysis of real-time speech translator smart module. In: Proc. 4th Int’l Symposium on Wearable Computers (ISWC), pp. 25–32 (2000)Google Scholar
  32. 32.
    Zappi, P., Lombriser, C., Farella, E., Roggen, D., Benini, L., Tröster, G.: Activity recognition from on-body sensors: accuracy-power trade-off by dynamic sensor selection. In: Verdone, R. (ed.) EWSN 2008. LNCS, vol. 4913, pp. 17–33. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  33. 33.
    Polikar, R.: Ensemble based systems in decision making. IEEE Circuits and Systems Magazine 6(3), 21–45 (2006)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Claudia Villalonga
    • 1
    • 2
  • Daniel Roggen
    • 1
  • Clemens Lombriser
    • 1
  • Piero Zappi
    • 3
  • Gerhard Tröster
    • 1
  1. 1.Wearable Computing Lab.ETH ZürichSwitzerland
  2. 2.SAP ResearchCEC ZürichSwitzerland
  3. 3.DEISUniversity of BolognaItaly

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