Abstract
This article describes a conceptual hybrid architecture for a knowledge discovery system, able to automatically annotate, reason, classify and operate with sensor data. The adoption of semantic web technologies to enrich sensor and link data represents an adequate methodology that facilitates the processes of reasoning, classification and other types of automation. We discussed a system deployment scenario in the context of e-health.
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Negru, S. (2012). SemaKoDE: Hybrid System for Knowledge Discovery in Sensor-Based Smart Environments. In: Brambilla, M., Tokuda, T., Tolksdorf, R. (eds) Web Engineering. ICWE 2012. Lecture Notes in Computer Science, vol 7387. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31753-8_41
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DOI: https://doi.org/10.1007/978-3-642-31753-8_41
Publisher Name: Springer, Berlin, Heidelberg
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