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Reasoning for sensor data interpretation: an application to air quality monitoring
Örebro University, School of Science and Technology. (AASS)ORCID iD: 0000-0002-4001-2087
Örebro University, School of Science and Technology. (AASS)ORCID iD: 0000-0002-3122-693X
2015 (English)In: Journal of Ambient Intelligence and Smart Environments, ISSN 1876-1364, Vol. 7, no 4, 579-597 p.Article in journal (Refereed) Published
Abstract [en]

In this paper we introduce a representation and reasoning model for the interpretation of time-series signals of a gas sensor situated in a sensor network. The interpretation process includes inferring high level explanations for changes detected over the gas signals. Inspired from the Semantic Sensor Network (SSN), the ontology used in this work provides an adaptive way of modelling the domain-related knowledge. Furthermore, exploiting (Incremental) Answer Set Programming (ASP) enables a declarative and automatic way of rule definition. Converting the ontology concepts and relations into ASP logic programs, the interpretation process defines a logic program whose answer sets are considered as eventual explanations for the detected changes in the gas sensor signals. The proposed approach is tested in a kitchen environment which contains several objects monitored by different sensors. The contextual information provided by the sensor network together with high level domain knowledge are used to infer explanations for changes in the ambient air detected by the gas sensors.

Place, publisher, year, edition, pages
2015. Vol. 7, no 4, 579-597 p.
Keyword [en]
Semantic sensor ontology, non-monotonic reasoning, answer set programming, knowledge representation
National Category
Computer Science
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-45544DOI: 10.3233/AIS-150323ISI: 000357989200011OAI: oai:DiVA.org:oru-45544DiVA: diva2:845498
Available from: 2015-08-12 Created: 2015-08-12 Last updated: 2017-10-17Bibliographically approved

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Alirezaie, MarjanLoutfi, Amy
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CiteExportLink to record
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Citation style
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