Reasoning for sensor data interpretation: An application to air quality monitoring

Article type: Research Article

Authors: Alirezaie, Marjan^{; *} | Loutfi, Amy

Affiliations: Center for Applied Autonomous Sensor Systems (AASS), Dept. of Science and Technology, Örebro University, SE-701 82, Örebro, Sweden. E-mails: [email protected], [email protected]

Correspondence: [*] Corresponding author. E-mail: [email protected].

Abstract: 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 monitoredby 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.

Keywords: Semantic sensor ontology, non-monotonic reasoning, answer set programming, knowledge representation

DOI: 10.3233/AIS-150323

Journal: Journal of Ambient Intelligence and Smart Environments, vol. 7, no. 4, pp. 579-597, 2015