Abstract
In this paper we describe a novel methodology for performing real-time analysis of localization data streams produced by sensors embedded in ambient intelligence (AmI) environments. The methodology aims to handle different types of real-time events, detect interesting behavior in sequences of such events, and calculate statistical information using a scalable stream-processing engine (SPE) that executes continuous queries expressed in a stream-oriented query language. Key contributions of our approach are the integration of the Borealis SPE into a large-scale interactive museum exhibit system that tracks visitor positions through a number of cameras; the extension and customization of Borealis to support the types of real-time analysis useful in the context of the museum exhibit as well as in other AmI applications; and the integration with a visualization component responsible for rendering events received by the SPE in a variety of human readable forms.
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© 2011 Springer-Verlag Berlin Heidelberg
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Stamatakis, D., Grammenos, D., Magoutis, K. (2011). Real-Time Analysis of Localization Data Streams for Ambient Intelligence Environments. In: Keyson, D.V., et al. Ambient Intelligence. AmI 2011. Lecture Notes in Computer Science, vol 7040. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25167-2_10
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DOI: https://doi.org/10.1007/978-3-642-25167-2_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-25166-5
Online ISBN: 978-3-642-25167-2
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