Paper 89 (Research track)

CEMID: A Semantic Based Framework for Complex Events Modeling and Detection in Multimedia Sensor Networks

Author(s): Chinnapong Angsuchotmetee, Richard Chbeir, Yudith Cardinale, Shohei Yokoyama

Abstract: In Multimedia Sensor Networks (MSNs), gathered readings are enriched with multimedia data which can be used for detecting more complex and application-meaningful events, compared with using solely scalar sensors. However, the main challenge is the difficulty in translating all gathered data into events. We propose CEMID, a semantic-based framework to support Complex Events ModelIng and Detection in MSNs, which relies on: (i) MSSN-Onto, an ontology-based data model for modeling MSNs; (ii) the CEMiD language for defining MSNs and events; and (iii) a semantic-based event processing engine. CEMID allows users to model MSN infrastructure and events, and then dynamically detects events in near real time according to the provided models. We validate CEMID by experimentation. Results show that it can properly detect events in a high-work load scenario with the detection latency of less than one second.

Keywords: multimedia sensor network; atomic/complex event; event processing

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