An Ontology – based Contextual Approach for Cross-domain Applications in Internet of Things
DOI:
https://doi.org/10.31449/inf.v46i5.3627Abstract
The Internet of Things is an ecosystem which enables objects and devices such as sensors or actuators to communicate and exchange information with each other without human intervention. One of the main challenges in the Internet of Things is the lack of semantic interoperability; devices cannot understand the meaning of raw data, due to the diversity and heterogeneity in data formats from different sources. In order to deal with semantic interoperability, the ontologies are the one way to integrate semantics to raw data; they describe an IoT system and represent the data in a standardized way. The IoT devices provide a great deal of IoT data, mainly used for specific IoT applications such as smart home, smart farming, smart cities or healthcare. Therefore, existing applications became isolated in vertical silos, each one of them use independently their own model (i.e. ontology), which makes this ontologies also limited to a specific domain. Our approach has the goal of breaking down these vertical silos and achieves a semantic interoperability across IoT domains in cross-domain applications. In this paper, we have proposed a development of a single cross-domain ontology named CDOnto, it is considered to be a generic across different IoT domains, which can be extended by domain-specific ontologies. The proposed model follows a contextual approach to organize and distinguish the combined domains (i.e. contexts) representations. In addition, the ontology allows reasoning across overlapping domains and infers a complementary and new knowledge required in cross-domain applications.References
Almeida, A., Lo´pez-de Ipin˜a, D., (2012). Assessing ambiguity of context data in intelligent environments: Towards a more reliable context managing system. Sensors 12, 4934–4951.
Ardjani, F., (2015). Ontology-alignment techniques: Survey and analysis. International Journal of Modern Education and Computer Science 11, 67–78.
Bajaj, G., Agarwal, R., Singh, P., Georgantas, N., Issarny, V., (2017). A study of existing ontologies in the iot-domain. arXiv preprint arXiv:1707.00112 .
Benslimane, D., Arara, A., Falquet, G., Maamar, Z., Thiran, P., Gargouri, F., (2006). Contextual ontologies, in: International Conference on Advances in Information Systems, Springer. pp. 168–176.
Borgida, A., Serafini, L., (2003). Distributed description logics: Assimilating information from peer sources, in: Journal on data semantics I. Springer, pp. 153–184.
Bouquet, P., Giunchiglia, F., Van Harmelen, F., Serafini, L., Stuckenschmidt, H., (2003). C-owl: Contextualizing ontologies, in: International Semantic Web Conference, Springer. pp. 164–179.
Bouquet, P., Giunchiglia, F., Van Harmelen, F., Serafini, L., Stuckenschmidt, H., (2004). Contextualizing ontologies. Journal of Web Semantics 1, 325–343.
Daniele, L., den Hartog, F., Roes, J., (2015). Created in close interaction with the industry: the smart appliances reference (saref) ontology, in: International Workshop Formal Ontologies Meet Industries, Springer. pp. 100–112.
Daniele, L., Solanki, M., den Hartog, F., Roes, J., (2016). Interoperability for smart appliances in the iot world, in: International Semantic Web Conference, Springer. pp. 21–29.
Dey, S., Dasgupta, R., (2014). Sensor knowledge representation with spatiotemporal annotation: An energy sensor ontology use case, in: IEEE International Conference on Pervasive Computing and Communication Workshops (PERCOM WORKSHOPS), IEEE. pp. 455–459.
Gyrard, A., (2013). A machine-to-machine architecture to merge semantic sensor measurements, in: Proceedings of the 22nd International Conference on World Wide Web, pp. 371–376.
Hemam, M., (2018). An extension of the ontology web language with multi-viewpoints and probabilistic reasoning. International Journal of Advanced Intelligence Paradigms 10, 247–265.
Huang, X., Yi, J., Zhu, X., Chen, S., (2016). A semantic approach with decision support for safety service in smart home management. Sensors 16. URL: https://www.mdpi.com/1424-8220/16/8/1224.
Lee, K., Lee, J., Kwan, M.P., (2017). Location-based service using ontology-based semantic queries: A study with a focus on indoor activities in a university context. Computers, Environment and Urban Systems 62, 41–52.
Mishra, S., Jain, S., (2020). Ontologies as a semantic model in iot. International Journal of Computers and Applications 42, 233–243.
Okeyo, G., Chen, L., Wang, H., Sterritt, R., (2014). Dynamic sensor data segmentation for real-time knowledge-driven activity recognition. Pervasive and Mobile Computing 10, 155–172.
Ozaki, A., (2020). Learning description logic ontologies: Five approaches. Where do they stand ? KI-Ku¨nstliche Intelligenz 34, 317–327.
Seydoux, N., Drira, K., Hernandez, N., Monteil, T., (2016). Iot-o, a core-domain iot ontology to represent connected devices networks, in: European Knowledge Acquisition Workshop, Springer. pp. 561–576.
Sudhana, K.M., Raj, V.C., Suresh, R., (2013). An ontology-based framework for context-aware adaptive e-learning system, in: International Conference on Computer Communication and Informatics, IEEE. pp. 1–6.
Venkatesh, J., Chan, C., Akyurek, A.S., Rosing, T.S., (2016). A modular approach to context-aware iot applications, in: IEEE First International Conference on Internet-of-Things Design and Implementation (IoTDI), IEEE. pp. 235–240.
Wang, X., Ji, Q., (2012). Learning dynamic bayesian network discriminatively for human activity recognition, in: Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012), IEEE. pp. 3553–3556.
Woznowski, P.R., Tonkin, E.L., Flach, P.A., (2018). Activities of daily living ontology for ubiquitous systems: Development and evaluation. Sensors 18, 2361.
Downloads
Published
How to Cite
Issue
Section
License
I assign to Informatica, An International Journal of Computing and Informatics ("Journal") the copyright in the manuscript identified above and any additional material (figures, tables, illustrations, software or other information intended for publication) submitted as part of or as a supplement to the manuscript ("Paper") in all forms and media throughout the world, in all languages, for the full term of copyright, effective when and if the article is accepted for publication. This transfer includes the right to reproduce and/or to distribute the Paper to other journals or digital libraries in electronic and online forms and systems.
I understand that I retain the rights to use the pre-prints, off-prints, accepted manuscript and published journal Paper for personal use, scholarly purposes and internal institutional use.
In certain cases, I can ask for retaining the publishing rights of the Paper. The Journal can permit or deny the request for publishing rights, to which I fully agree.
I declare that the submitted Paper is original, has been written by the stated authors and has not been published elsewhere nor is currently being considered for publication by any other journal and will not be submitted for such review while under review by this Journal. The Paper contains no material that violates proprietary rights of any other person or entity. I have obtained written permission from copyright owners for any excerpts from copyrighted works that are included and have credited the sources in my article. I have informed the co-author(s) of the terms of this publishing agreement.
Copyright © Slovenian Society Informatika