Modeling and reasoning of IoT architecture in semantic ontology dimension Abstract   The architecture for IoT is the primary foundation for designing and implementing the System of Internet of things. This paper discusses the theory, method, tools and practice of modeling and reasoning the architecture of the Internet of Things system from the dimension of semantic ontology. This paper breaks the way of static ontology modeling, and proposes an implementation framework for realtime and dynamic ontology modeling of the IoT system from the running system. According to the actual needs of the health cabin IoT system and the combination of theory and practice, the system architecture model of the semantic ontology dimension of IoT is built. Then, based on the reasoning rules of the ontology model, the model is reasoned by Pellet reasoning engine which injects the atom of the custom reasoning builtins into the source code. In this way we have realized the automatic classification and attribute improvement of resources and behaviors of the IoT system, the realtime working state detection and fault diagnosis of the IoT system, and the automatic control of the IoT system and resources.

Cutting a Path Through the IoT Ontology Jungle  A MetaSurvey Interoperability of InternetofThings(IoT) applications, being characterized by massive heterogeneity of xe2x80x9cthingsxe2x80x9d, has become a key challenge in IoT research due to the omnipresence of smart devices. In order to achieve adequate interoperability levels, semantic technologies in terms of ontologies are a promising paradigm. Due to the plethora of IoT ontologies available, one gets, however, easily lost in the ontology jungle due to the lack of an overall and uptodate view on the IoT ontology landscape. In this respect, the aim of this paper is to act as an umbrella across several uptodate IoT ontology survey papers in terms of a metasurvey comprising a threefold contribution: Firstly, addressing the survey landscape, we provide insight into commonalities and differences regarding the scope of eight survey papers and their rationale behind. Secondly, addressing the IoT ontology landscape, we analyze the IoT ontologies discussed in the survey papers on basis of quantitative and qualitative aspects. Thirdly, addressing the stateofresearch of ontologies for IoT, we identify commonalities and differences regarding conclusions and lessons learned of the survey papers.