An Application of Context Middleware Based on Fuzzy Logic for Wireless Sensor Networks
Ye NING, Ruchuan WANG, Shouming MA, Zhili WANG
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DOI: 10.4236/wsn.2009.15045   PDF    HTML     5,131 Downloads   9,829 Views   Citations

Abstract

The research of context-aware computing based on wireless sensor network (WSN) aims at intelligently connecting computers, users, and environment. So its application system should be flexibly adaptable to dynamic changes of context and application requirements and proactively provides the information satisfied with current context for users. The middleware can be very effective to provide the support runtime services for context-aware computing. In this paper we propose middleware architecture for context processing. This architecture is based on fuzzy logic control (FLC) system for context reasoning and sensor fusion. We propose a formal context representation model in which a user’s context is described by a set of roles and relations correspond to a context space. A middleware prototype has been developed, which detect tourist’ physical context and provide reminding. The experiments prove that the model and approach proposed are feasible.

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Y. NING, R. WANG, S. MA and Z. WANG, "An Application of Context Middleware Based on Fuzzy Logic for Wireless Sensor Networks," Wireless Sensor Network, Vol. 1 No. 5, 2009, pp. 365-369. doi: 10.4236/wsn.2009.15045.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] B. Schilit and M. Theimer, “Disseminating active map information to mobile hosts,” IEEE Network, Vol. 8, No. 5, pp. 22–32, 1994.
[2] P. Dourish, “What we talk about when we talk about context,” Personal and Ubiquitous Computing, Vol. 8, No. 1, pp. 19–30, 2004.
[3] A. Helal, “Programming pervasive spaces,” The Standards and Emerging Technologies Department, IEEE Pervasive Computing magazine, Sumi Helal, Dept. Editor, Vol. 4, No. 1, January–March 2005.
[4] H. J. Zimmermann, “Fuzzy sets theory and its applications,” Second, revised edition, Kluwer Academic Publishers, 1991.
[5] H. Wu, M. Siegel, and S. Ablay, “Sensor fusion for context understanding,” Instrumentation and Measurement Technology Conference, IMTC/2002, Proceedings of the 19th IEEE, Vol. 1, pp. 13–17, May 2002.
[6] M. Roman, C. K. H., R. Cerqueira, et al, “Gaia: A middleware infrastructure to enable active spaces,” IEEE Pervasive Computing, pp. 74–83, 2002.
[7] Microsoft Research, “Easy living,” 2009, http://research.microsoft.com/easyliving/.
[8] M. Roman, F. Kon, and R. H. Campbell, “Reflective middleware: From your desk to your hand,” IEEE DS Online (Special Issue on Reflective Middleware), 2001.
[9] S. Ou and K. Yang, “An effective offloading middleware for pervasive services on mobile devices,” Pervasive and Mobile Computing, Vol. 3, No. 4, pp. 362–385, 2007.
[10] A. Padovitz, et al, “An approach to data fusion for context awareness,” Fifth International Conference on Modelling and Using Context, CONTEXT’05, Paris, France, July 2005.
[11] M. Korkea-aho, “Context-aware applications survey,” 2009, http://www.hut.fi/~mkorkeaa/doc/context-aware.html.
[12] L. A. Zadeh, Fuzzy sets, Information and Control, pp. 338–353, 1965.
[13] M. Marin-Perianu, C. Lombriser, et al, “Distributed activity recognition with fuzzy enabled wireless sensor networks,” Technical Report TRCTIT-07-68, Enschede, September 2007.
[14] E. Hisdal, “The IF THEN ELSE statement and interval-valued fuzzy sets of higher type,” International Journal Man-Machine Studies, Vol. 35, pp. 385–455, 1981.
[15] Wireless Sensor Network Research Center of Nanjing University of Post and Telecommunications, “UbiCell product manuals,” 2009, http://www.wsns.net.cn.

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