Abstract
Urban environments are increasingly invaded by devices that acquire sensor information and pave the way for innovative forms of context awareness. Collecting knowledge from loosely-structured data streams and reasoning about changes are two key elements of the process. This paper illustrates a possible way to combine these two elements in a coordinated way. We make use of a recently-developed framework for classifying data streams with service-oriented, reconfigurable components. Furthermore, we embed the KnowLang Reasoner, allowing logical and statistical reasoning on the acquired knowledge aiming to achieve self-adaptation.
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© 2015 Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Bicocchi, N., Vassev, E., Zambonelli, F., Hinchey, M. (2015). Reasoning on Data Streams: An Approach to Adaptation in Pervasive Systems. In: Vinh, P., Vassev, E., Hinchey, M. (eds) Nature of Computation and Communication. ICTCC 2014. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 144. Springer, Cham. https://doi.org/10.1007/978-3-319-15392-6_3
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DOI: https://doi.org/10.1007/978-3-319-15392-6_3
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