Re-sculpturing Semantic Web of Things as a Strategy for Internet of Things’ Intrinsic Contradiction

In this paper, based on annotating objects’ information and reasoning semantically with ontologies, the strategy of Semantic Web of Things (SWoT) for Internet of Things’ intrinsic contradiction is extended, and machine learning is introduced so that a novel hierarchical structure and the dynamic relationship between entities are proposed on SWoT. Specific contributions: (1) Establish of vertical and hierarchical framework of SWoT; (2) Definite on composite ontologies and (3) construct computational framework of Agent-based dynamic relationship model. And this paper proposes the essence that SWoT should be attributed to the interoperability between its various objects, which constructs inter-objects’ certain dynamic relationships.