Towards Global IoT-enabled Smart Cities Interworking using Adaptive Semantic Adapter

JongGwan An, Franck Le Gall, Jaeho Kim, Jaeseok Yun, Jaeyoung Hwang, Martin Bauer, Mengxuan Zhao, JaeSeung Song, IEEE INTERNET OF THINGS JOURNAL, VOL. , NO. , 2019

Since the Internet-of-Things (IoT) has been introduced, it is considered as one of the emerging technologies providing great opportunities to many vertical industries. One of the major IoT application areas that gets significant attention is Smart City. Since it is unrealistic to expect full convergence toward a single IoT platform in the near future, it is mandatory to enable interworking between different platforms based on
multiple standards, coexisting in the emerging Smart Cities. In this paper, we take the example of two global IoT standards, FIWARE and oneM2M, which are actively used in many Smart City projects, and analyze them to show the feasibility of IoT platforms interworking. Based on the analysis, we design and implement a novel IoT interworking architecture providing a semantic driven integration framework suitable for Smart City. The core idea behind our approach is to introduce interworking proxies that (1) conduct a static mapping of sensor information between IoT platforms; (2) perform semantic interoperability using semantically annotated resources via a semantic interworking proxy that dynamically discovers new kinds of information and adapts itself to enable automatic translation of semantic data between given source and target IoT platforms while it is running.
We present the system based on these proxies and evaluate it in Santander Smart City. The results demonstrate that it is able to discover and manage IoT sensors connected to both oneM2M and FIWARE. It appears that the semantic approach provides the flexibility and dynamic adaptivity needed for fast growing and rapidly changing urban environments.