University of Oulu

A. I. Maarala, X. Su and J. Riekki, "Semantic Reasoning for Context-Aware Internet of Things Applications," in IEEE Internet of Things Journal, vol. 4, no. 2, pp. 461-473, April 2017. doi: 10.1109/JIOT.2016.2587060

Semantic reasoning for context-aware internet of things applications

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Author: Maarala, Altti Ilari1,2; Su, Xiang3; Riekki, Jukka3
Organizations: 1Department of Computer Science and Engineering, University of Oulu, Oulu 90580, Finland
2Department of Computer Science, Aalto University, Espoo FI-00076, Finland
3Center for Ubiquitous Computing, University of Oulu, Oulu 90014, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.4 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2017
Publish Date: 2019-06-03


Acquiring knowledge from continuous and heterogeneous data streams is a prerequisite for Internet of Things (IoT) applications. Semantic technologies provide comprehensive tools and applicable methods for representing, integrating, and acquiring knowledge. However, resource-constraints, dynamics, mobility, scalability, and real-time requirements introduce challenges for applying these methods in IoT environments. We study how to utilize semantic IoT data for reasoning of actionable knowledge by applying state-of-the-art semantic technologies. For performing these studies, we have developed a semantic reasoning system operating in a realistic IoT environment. We evaluate the scalability of different reasoning approaches, including a single reasoner, distributed reasoners, mobile reasoners, and a hybrid of them. We evaluate latencies of reasoning introduced by different semantic data formats. We verify the capabilities of promising semantic technologies for IoT applications through comparing the scalability and real-time response of different reasoning approaches with various semantic data formats. Moreover, we evaluate different data aggregation strategies for integrating distributed IoT data for reasoning processes.

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Series: IEEE internet of things journal
ISSN: 2372-2541
ISSN-E: 2327-4662
ISSN-L: 2327-4662
Volume: 4
Issue: 2
Pages: 461 - 473
DOI: 10.1109/JIOT.2016.2587060
Type of Publication: A1 Journal article – refereed
Field of Science: 113 Computer and information sciences
213 Electronic, automation and communications engineering, electronics
Funding: This work was funded by the Finnish Funding Agency for Innovation (TEKES) as a part of the DIGILE’s Internet of Things program of Finland.
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