Perceptive Services Composition using semantic language and distributed knowledge

Rémi Emonet 1 Dominique Vaufreydaz 1
1 PRIMA - Perception, recognition and integration for observation of activity
Inria Grenoble - Rhône-Alpes, UJF - Université Joseph Fourier - Grenoble 1, INPG - Institut National Polytechnique de Grenoble , CNRS - Centre National de la Recherche Scientifique : UMR5217
Abstract : Building applications composing perceptive services in a pervasive environment can lead to an inextricable problem: they were built by several people, using different programming languages and multiple conventions and protocols. Moreover, services can be volatile, so appear or disappear during running time of the application. This paper proposes the use of a dedicated human-readable semantic language to describe perceptive services. After converting this description into a more common language, one can recruit services using inference engines to build complex applications. In order to increase robustness of the whole system, descriptions of services are distributed over the network using a crosslanguage crossplateform open-source middleware of our own called OMiSCID.
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https://hal.inria.fr/inria-00326679
Contributor : Dominique Vaufreydaz <>
Submitted on : Saturday, October 4, 2008 - 10:54:43 PM
Last modification on : Wednesday, April 11, 2018 - 1:52:48 AM
Long-term archiving on : Tuesday, June 28, 2011 - 5:01:14 PM

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Rémi Emonet, Dominique Vaufreydaz. Perceptive Services Composition using semantic language and distributed knowledge. Common Models and Patterns for Pervasive Computing at the 5th International Conference on Pervasive Computin, May 2007, Toronto (Ontario), Canada. ⟨inria-00326679⟩

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