Re-sculpturing Semantic Web of Things
as a Strategy for Internet of Things’ Intrinsic
Contradiction
Jingmin An
1(&)
, Guanyu Li
2(&) , Bo Ning
2 , Wei Jiang
2 ,
and Yunhao Sun
2
1 Faculty of Computer and Software, Dalian Neusoft University of Information,
Dalian, China
870457569@qq.com
2 Faculty of Information Science and Technology, Dalian Maritime University,
Dalian, China
rabitlee@163.com
Abstract. 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 Agentbased 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.
Keywords: Semantic Web of Things Á Interoperability Á Composite ontology Á
Agent Á Dynamic relationships
1 Introduction
Since the concept of Semantic Web of Things (SWoT) was put forward, it has been
generally believed that SWoT is the result which semantic technology is integrated into
the Internet of Things (IoT). In other words, use ontology to annotate the information
of objects in IoT, and infer the information in the network based on ontology, in order
to achieve global semantic consistency of information.
Ruta and Sciosci [1, 2] point out that SWoT is an organic integration of IoT and
Semantic Web (SW). Use pervasive computing to achieve resource sharing in IoT [3],
and SW technology can efficiently integrate and reuse resources of IoT. Semantic
technology-embedded IoT is utilized to share existing information and generate new
information by semantically reasoning. Ontology-based technology of knowledge
fusion can be implemented to integrate and share data and information in SWoT [4]. Jia
[4] and others reckon that the combination of ontology theory and IoT technology can
meet the needs of dynamic and distributed services. Huang and Li [5, 6] deeply analyze
© Springer Nature Singapore Pte Ltd. 2020
Q. Liang et al. (Eds.): Artificial Intelligence in China, LNEE 572, pp. 554–562, 2020.
https://doi.org/10.1007/978-981-15-0187-6_66
as a Strategy for Internet of Things’ Intrinsic
Contradiction
Jingmin An
1(&)
, Guanyu Li
2(&) , Bo Ning
2 , Wei Jiang
2 ,
and Yunhao Sun
2
1 Faculty of Computer and Software, Dalian Neusoft University of Information,
Dalian, China
870457569@qq.com
2 Faculty of Information Science and Technology, Dalian Maritime University,
Dalian, China
rabitlee@163.com
Abstract. 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 Agentbased 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.
Keywords: Semantic Web of Things Á Interoperability Á Composite ontology Á
Agent Á Dynamic relationships
1 Introduction
Since the concept of Semantic Web of Things (SWoT) was put forward, it has been
generally believed that SWoT is the result which semantic technology is integrated into
the Internet of Things (IoT). In other words, use ontology to annotate the information
of objects in IoT, and infer the information in the network based on ontology, in order
to achieve global semantic consistency of information.
Ruta and Sciosci [1, 2] point out that SWoT is an organic integration of IoT and
Semantic Web (SW). Use pervasive computing to achieve resource sharing in IoT [3],
and SW technology can efficiently integrate and reuse resources of IoT. Semantic
technology-embedded IoT is utilized to share existing information and generate new
information by semantically reasoning. Ontology-based technology of knowledge
fusion can be implemented to integrate and share data and information in SWoT [4]. Jia
[4] and others reckon that the combination of ontology theory and IoT technology can
meet the needs of dynamic and distributed services. Huang and Li [5, 6] deeply analyze
© Springer Nature Singapore Pte Ltd. 2020
Q. Liang et al. (Eds.): Artificial Intelligence in China, LNEE 572, pp. 554–562, 2020.
https://doi.org/10.1007/978-981-15-0187-6_66