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A Method for Identifying and Evaluating Architectures of Intelligent Goods Services

  • Åse Jevinger
  • Paul Davidsson
  • Jan A. Persson
Part of the Studies in Computational Intelligence book series (SCI, volume 382)

Abstract

This paper presents a method for identifying possible architectural solutions for potential intelligent goods services. The solutions range from putting all intelligence at the goods level, to requiring no intelligence on the goods at all. The method is based on a general framework for describing intelligent goods systems, which involves several levels of intelligence related to both the goods and the local environments surrounding the goods. Furthermore, a number of quality attributes are identified, which may be used for evaluating and comparing the solutions. Based on these attributes, a quality evaluation of the architectural solutions related to a potential intelligent goods service is also provided, as an example.

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References

  1. 1.
    Davidsson, P., Johansson, S., Svahnberg, M.: Using the analytic hierarchy process for evaluating multi-agent system architecture candidates. In: Müller, J.P., Zambonelli, F. (eds.) AOSE 2005. LNCS, vol. 3950, pp. 205–217. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  2. 2.
    Hong, L., Hickman, M., Weissenberger, S.: A structured approach for ITS architecture representation and evaluation. In: IEEE 6th International Conference on Vehicular Navigation and Information Systems, pp. 442–449. IEEE, Los Alamitos (1995)Google Scholar
  3. 3.
    Huschebeck, M., Piers, R., Mans, D., Schygulla, M., Wild, D.: ICSS - Impact assessment study on the introduction of intelligent cargo systems in transport logistics industry, http://www.intelligentcargo.eu/ (cited April 1, 2009)
  4. 4.
    Jevinger, Å., Davidsson, P., Persson, J.A.: Agent based intelligent goods. In: 6th Workshop on Agents in Traffic and Transportation@AAMAS (2010)Google Scholar
  5. 5.
    McFarlane, D., Sarma, S., Chirn, J.L., Wong, C.Y., Ashton, K.: Auto ID systems and intelligent manufacturing control. Journal of Engineering Applications of Artificial Intelligence 16(4), 365–376 (2003)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Åse Jevinger
    • 1
  • Paul Davidsson
    • 2
  • Jan A. Persson
    • 2
  1. 1.Blekinge Instisute of TechnologyKarlshamnSweden
  2. 2.Malmö UniversityMalmöSweden

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