Abstract
In this paper we present our work in a real-time, context-aware system, applied in a smart classroom domain, which aims to assist its users after recognizing any occurring activity. We exploit the advantages of ontologies in order to model the context and introduce as well a method for extracting information from an ontology and using it in a machine learning dataset. This method enables real-time reasoning on high-level-activities recognition. We describe the overview of our system as well as a typical usage scenario to indicate how our system would react in this specific situation. An experimental evaluation of our system in a real, publicly available lecture is also presented.
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Maria, K., Vasilis, E., Grigoris, A. (2012). S-CRETA: Smart Classroom Real-Time Assistance. In: Novais, P., Hallenborg, K., Tapia, D., RodrÃguez, J. (eds) Ambient Intelligence - Software and Applications. Advances in Intelligent and Soft Computing, vol 153. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28783-1_9
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DOI: https://doi.org/10.1007/978-3-642-28783-1_9
Publisher Name: Springer, Berlin, Heidelberg
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