Journal of Beijing University of Posts and Telecommunications

  • EI核心期刊

JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM ›› 2017, Vol. 40 ›› Issue (4): 104-110.doi: 10.13190/j.jbupt.2017.04.017

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A Knowledge Annotation and Reasoning Semantic Web of Things Framework for Intelligent Diagnosis

YANG Yu-nong, WU Zhen-yu, ZHU Xin-ning   

  1. School of Information and Communication, Beijing University of Posts and Telecommunications, Beijing 100876, China
  • Received:2017-03-22 Online:2017-08-28 Published:2017-07-10

Abstract: The web of things(WoT) is one of the present advancements in which devices, objects, and sensors are getting linked to the semantic web. To solve the integration problems in developing WoT application with huge device data. A semantic annotation and reasoning based framework and approach was proposed. It presents a universal ontology for WoT applications with expanding a physical process model on the basis of reusing the traditional device description ontology. The framework also shows that semantic sensor networks, semantic web technologies, as well as reasoning mechanisms can help in real-world applications to automatically derive complex models for analytics tasks such as anomaly diagnosis and automatic control. The article demonstrates approaches for building automation system with numerous connected devices in knowledge base constructing and show how the semantic framework allows us to develop a complex WoT application.

Key words: WoT knowledge base, semantic rules and reasoning, entity linking, anomaly diagnosis

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