Abstract
The growth and proliferation of technologies in the field of sensor networking and mobile computing have led to the emergence of diverse applications that process and analyze sensory data on mobile devices such as a smart phone. However, the real power to make a significant impact on the area of developing these applications rests not merely on deploying the technologies, but on the ability to perform real-time, intelligent analysis of the data streams that are generated by the various sensors. In this chapter, we present a novel approach for Situation-Aware Adaptive Processing (SAAP) of data streams for pervasive computing environments. This approach uses fuzzy logic principles for modelling and reasoning about uncertain situations, and performs gradual adaptation of parameters of data stream mining algorithms in real-time according to availability of resources and the occurring situations.
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Haghighi, P.D., Gaber, M.M., Krishnaswamy, S., Zaslavsky, A. (2009). Situation-Aware Adaptive Processing (SAAP) of Data Streams. In: Hassanien, AE., Abawajy, J., Abraham, A., Hagras, H. (eds) Pervasive Computing. Computer Communications and Networks. Springer, London. https://doi.org/10.1007/978-1-84882-599-4_14
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DOI: https://doi.org/10.1007/978-1-84882-599-4_14
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