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Wireless Communications and Mobile Computing
Volume 2017, Article ID 9731806, 10 pages
https://doi.org/10.1155/2017/9731806
Research Article

Semantic Interoperability in Heterogeneous IoT Infrastructure for Healthcare

1School of Computer Science and Engineering, Kyungpook National University, Daegu, Republic of Korea
2Department of Computer Science, COMSATS Institute of Information Technology, Sahiwal, Pakistan
3Department of Computer Engineering, Bahria University, Islamabad, Pakistan

Correspondence should be addressed to Kijun Han; rk.ca.unk@nahjk

Received 21 December 2016; Accepted 6 February 2017; Published 5 March 2017

Academic Editor: Yoshikazu Miyanaga

Copyright © 2017 Sohail Jabbar et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Interoperability remains a significant burden to the developers of Internet of Things’ Systems. This is due to the fact that the IoT devices are highly heterogeneous in terms of underlying communication protocols, data formats, and technologies. Secondly due to lack of worldwide acceptable standards, interoperability tools remain limited. In this paper, we proposed an IoT based Semantic Interoperability Model (IoT-SIM) to provide Semantic Interoperability among heterogeneous IoT devices in healthcare domain. Physicians communicate their patients with heterogeneous IoT devices to monitor their current health status. Information between physician and patient is semantically annotated and communicated in a meaningful way. A lightweight model for semantic annotation of data using heterogeneous devices in IoT is proposed to provide annotations for data. Resource Description Framework (RDF) is a semantic web framework that is used to relate things using triples to make it semantically meaningful. RDF annotated patients’ data has made it semantically interoperable. SPARQL query is used to extract records from RDF graph. For simulation of system, we used Tableau, Gruff-6.2.0, and Mysql tools.