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, informatics and engineering, among many others. Much of the IoT initiative is supported by the capabilities of manufacturing low-cost and energy-efficient hardware for devices with communication capacities (e.g., sensors and RFID tags), the maturity of wireless sensor network technologies, and the interests in integrating the physical and cyber worlds. IoT consists of interconnected "Things" and their virtual representations addressable by using standard communication protocols. 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. The semantic Web community has worked on combining knowledge engineering and AI techniques to represent, integrate, and reason upon data and knowledge in the past decades. Semantic technologies based on machineinterpretable representation formalism have shown promise for describing objects, sharing and integrating information, and infering new knowledge together with other intelligent processing techniques. The addition of semantics has also helped create machine-interpretable and self-descriptive data in the IoT domain. 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 we review some of the recent developments on applying the semantic technologies to IoT -in particular, information modeling, ontology design, and processing of semantic data -and discuss the challenges.
As highlighted by Barnaghi et al. REF , the heterogeneity of devices makes interoperability a challenging problem, which prevents generic solutions from being adopted on a global scale.
Semantics for the Internet of Things: Early Progress and Back to the Future
Int. J. Semantic Web Inf. Syst.
Int. J. Semantic Web Inf. Syst.
Computer Science