Semantic-driven configuration of Internet of Things middleware

Perera, Charith ORCID: https://orcid.org/0000-0002-0190-3346, Zaslavsky, Arkady, Compton, Michael, Christen, Peter and Georgakopoulos, Dimitrios 2013. Semantic-driven configuration of Internet of Things middleware. Presented at: 2013 Ninth International Conference on Semantics, Knowledge and Grids, Beijing, China, 3-4 October 2013. 2013 Ninth International Conference on Semantics, Knowledge and Grids. IEEE, pp. 66-73. 10.1109/SKG.2013.9

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Abstract

We are currently observing emerging solutions to enable the Internet of Things (IoT). Efficient and feature rich IoT middeware platforms are key enablers for IoT. However, due to complexity, most of these middleware platforms are designed to be used by IT experts. In this paper, we propose a semantics-driven model that allows non-IT experts (e.g. plant scientist, city planner) to configure IoT middleware components easier and faster. Such tools allow them to retrieve the data they want without knowing the underlying technical details of the sensors and the data processing components. We propose a Context Aware Sensor Configuration Model (CASCoM) to address the challenge of automated context-aware configuration of filtering, fusion, and reasoning mechanisms in IoT middleware according to the problems at hand. We incorporate semantic technologies in solving the above challenges. We demonstrate the feasibility and the scalability of our approach through a prototype implementation based on an IoT middleware called Global Sensor Networks (GSN), though our model can be generalized into any other middleware platform. We evaluate CASCoM in agriculture domain and measure both performance in terms of usability and computational complexity.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Publication
Status:	Published
Schools:	Computer Science & Informatics
Subjects:	Q Science > QA Mathematics > QA76 Computer software
Publisher:	IEEE
ISBN:	9781479930128
Date of First Compliant Deposit:	10 August 2020
Last Modified:	30 Jan 2023 09:45
URI:	https://orca.cardiff.ac.uk/id/eprint/134053

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