HSSN: an ontology for hybrid semantic sensor networks

Abstract : Semantic web techniques (e.g., ontologies) have been recently adopted for sensor network modeling. However, existing works do not fully address these challenges: (i) representing different sensor types (e.g., mobile/static sensors) to enrich the network with different data and ensure better coverage; (ii) representing a variety of platforms (e.g., environments, devices) for sensor deployment, thus, integrating new components (e.g., mobile phones); (iii) representing the diverse data (scalar/multimedia) needed for various applications (e.g., event detection); and (iv) proposing a generic model to allow re-usability in various application domains. In this paper, we propose HSSN, an ontology that extends the Semantic Sensor Network (SSN) ontology which is already re-usable and considers various platforms. We extend the representation of sensors, sensed data, and deployment environments to cope with these challenges. We evaluate the consistency, accuracy, clarity, and performance of HSSN.
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Conference papers
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https://hal.archives-ouvertes.fr/hal-02295950
Contributor : Elio Mansour <>
Submitted on : Tuesday, September 24, 2019 - 4:19:21 PM
Last modification on : Saturday, October 19, 2019 - 1:23:53 AM

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Elio Mansour, Richard Chbeir, Philippe Arnould. HSSN: an ontology for hybrid semantic sensor networks. the 23rd International Database Applications & Engineering Symposium, Jun 2019, Athènes, Greece. pp.8, ⟨10.1145/3331076.3331102⟩. ⟨hal-02295950⟩

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