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Semantics for the Internet of Things: Early Progress and Back to the Future

Author

Listed:
  • Payam Barnaghi

    (University of Surrey, UK)

  • Wei Wang

    (University of Surrey, UK)

  • Cory Henson

    (Wright State University, USA)

  • Kerry Taylor

    (Commonwealth Scientific and Industrial Research Organisation, ICT Centre, Australia)

Abstract

The Internet of Things (IoT) has recently received considerable interest from both academia and industry that are working on technologies to develop the future Internet. It is a joint and complex discipline that requires synergetic efforts from several communities such as telecommunication industry, device manufacturers, semantic Web, and informatics and engineering. Much of the IoT initiative is supported by the capabilities of manufacturing low-cost and energy-efficient hardware for devices with communication capacities, the maturity of wireless sensor network technologies, and the interests in integrating the physical and cyber worlds. However, the heterogeneity of the “Things” makes interoperability among them a challenging problem, which prevents generic solutions from being adopted on a global scale. Furthermore, the volume, velocity and volatility of the IoT data impose significant challenges to existing information systems. Semantic technologies based on machine-interpretable representation formalism have shown promise for describing objects, sharing and integrating information, and inferring new knowledge together with other intelligent processing techniques. However, the dynamic and resource-constrained nature of the IoT requires special design considerations to be taken into account to effectively apply the semantic technologies on the real world data. In this article the authors review some of the recent developments on applying the semantic technologies to IoT.

Suggested Citation

  • Payam Barnaghi & Wei Wang & Cory Henson & Kerry Taylor, 2012. "Semantics for the Internet of Things: Early Progress and Back to the Future," International Journal on Semantic Web and Information Systems (IJSWIS), IGI Global, vol. 8(1), pages 1-21, January.
  • Handle: RePEc:igg:jswis0:v:8:y:2012:i:1:p:1-21
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    Citations

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    Cited by:

    1. Zhaoyu Li & Rui Xu & Pingyuan Cui & Lida Xu & Wu He, 0. "Geometry-based propagation of temporal constraints," Information Systems Frontiers, Springer, vol. 0, pages 1-14.
    2. Zhang, Chuan & Romagnoli, Alessandro & Zhou, Li & Kraft, Markus, 2017. "Knowledge management of eco-industrial park for efficient energy utilization through ontology-based approach," Applied Energy, Elsevier, vol. 204(C), pages 1412-1421.
    3. Andreas Eigner & Christian Stary, 2023. "The Role of Internet-of-Things for Service Transformation," SAGE Open, , vol. 13(1), pages 21582440231, March.
    4. Zhaoyu Li & Rui Xu & Pingyuan Cui & Lida Xu & Wu He, 2017. "Geometry-based propagation of temporal constraints," Information Systems Frontiers, Springer, vol. 19(4), pages 855-868, August.
    5. Abderahman Rejeb & John G. Keogh & Wayne Martindale & Damion Dooley & Edward Smart & Steven Simske & Samuel Fosso Wamba & John G. Breslin & Kosala Yapa Bandara & Subhasis Thakur & Kelly Liu & Bridgett, 2022. "Charting Past, Present, and Future Research in the Semantic Web and Interoperability," Future Internet, MDPI, vol. 14(6), pages 1-32, May.
    6. Tohanean Dragos & Vasilescu Anca, 2019. "Business Models and Internet of Things," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 13(1), pages 1192-1203, May.
    7. Gergely Marcell Honti & Janos Abonyi, 2019. "A Review of Semantic Sensor Technologies in Internet of Things Architectures," Complexity, Hindawi, vol. 2019, pages 1-21, June.
    8. Alraja, Mansour, 2022. "Frontline healthcare providers’ behavioural intention to Internet of Things (IoT)-enabled healthcare applications: A gender-based, cross-generational study," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    9. Zhang, Junsheng & Sun, Yunchuan & Jara, Antonio J., 2015. "Towards semantically linked multilingual corpus," International Journal of Information Management, Elsevier, vol. 35(3), pages 387-395.

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