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Open AccessArticle

A Decentralized Semantic Reasoning Approach for the Detection and Representation of Continuous Spatial Dynamic Phenomena in Wireless Sensor Networks

1
Centre de Recherche en Données et Intelligence géOspatiales (CRDIG), 0611 Pavillon Casault Université Laval, Québec City, QC G1K 7P4, Canada
2
GéoSémantic Research, Sherbrooke, QC J1L 1W8, Canada
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Author to whom correspondence should be addressed.
Academic Editors: Eliseo Clementini and Wolfgang Kainz
ISPRS Int. J. Geo-Inf. 2021, 10(3), 182; https://doi.org/10.3390/ijgi10030182
Received: 24 January 2021 / Revised: 10 March 2021 / Accepted: 14 March 2021 / Published: 19 March 2021
(This article belongs to the Special Issue Applications of Discrete and Computational Geometry to Geoprocessing)
In this paper, we propose a decentralized semantic reasoning approach for modeling vague spatial objects from sensor network data describing vague shape phenomena, such as forest fire, air pollution, traffic noise, etc. This is a challenging problem as it necessitates appropriate aggregation of sensor data and their update with respect to the evolution of the state of the phenomena to be represented. Sensor data are generally poorly provided in terms of semantic information. Hence, the proposed approach starts with building a knowledge base integrating sensor and domain ontologies and then uses fuzzy rules to extract three-valued spatial qualitative information expressing the relative position of each sensor with respect to the monitored phenomenon’s extent. The observed phenomena are modeled using a fuzzy-crisp type spatial object made of a kernel and a conjecture part, which is a more realistic spatial representation for such vague shape environmental phenomena. The second step of our approach uses decentralized computing techniques to infer boundary detection and vertices for the kernel and conjecture parts of spatial objects using fuzzy IF-THEN rules. Finally, we present a case study for urban noise pollution monitoring by a sensor network, which is implemented in Netlogo to illustrate the validity of the proposed approach. View Full-Text
Keywords: sensor network; environmental monitoring; vague spatial object; three-valued logic; fuzzy reasoning sensor network; environmental monitoring; vague spatial object; three-valued logic; fuzzy reasoning
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MDPI and ACS Style

Ntankouo Njila, R.C.; Mostafavi, M.A.; Brodeur, J. A Decentralized Semantic Reasoning Approach for the Detection and Representation of Continuous Spatial Dynamic Phenomena in Wireless Sensor Networks. ISPRS Int. J. Geo-Inf. 2021, 10, 182. https://doi.org/10.3390/ijgi10030182

AMA Style

Ntankouo Njila RC, Mostafavi MA, Brodeur J. A Decentralized Semantic Reasoning Approach for the Detection and Representation of Continuous Spatial Dynamic Phenomena in Wireless Sensor Networks. ISPRS International Journal of Geo-Information. 2021; 10(3):182. https://doi.org/10.3390/ijgi10030182

Chicago/Turabian Style

Ntankouo Njila, Roger C.; Mostafavi, Mir A.; Brodeur, Jean. 2021. "A Decentralized Semantic Reasoning Approach for the Detection and Representation of Continuous Spatial Dynamic Phenomena in Wireless Sensor Networks" ISPRS Int. J. Geo-Inf. 10, no. 3: 182. https://doi.org/10.3390/ijgi10030182

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