Intelligent equipment design assisted by Cognitive Internet of Things and industrial big data

  • Jiafu Wan
  • Jiapeng Li
  • Qingsong HuaEmail author
  • Antonio Celesti
  • Zhongren Wang
S.I. : Cognitive Computing for Intelligent Application and Service


In recent years, the development of emerging technologies has brought about a new era of industrial reform. The current industrial revolution will deeply integrate the new generation of information technology with modern manufacturing industry and production servicing businesses to promote transformation and upgrading. As it is the foundation of the manufacturing industry, intelligent equipment plays an important role in the reform. In this paper, we propose an innovative design method to help design intelligent equipment. Firstly, referring to the architecture of the Cognitive Internet of Things (CIoT) and industrial big data, we proposed the architecture of the method and defined the different layers to process the data. Then, for the acquired external data, we put forward an algorithm which was combined with the technology of CIoT and industrial big data, to help designers analyze and make decisions. Finally, we verified the validity and feasibility of this method through a case study. The results showed that this method could effectively mine the deep information of intelligent equipment and provide more valuable information about design-assisting designers in designing better intelligent equipment.


Cognitive Internet of Things Industrial big data Intelligent equipment 



This work was supported in part by the National Key Research and Development Program of China (No. 2017YFE0101000), the Science and Technology Program of Guangzhou, China (No. 201802030005), the Joint Fund of the National Natural Science Foundation of China and Guangdong Province (No. U180120020), the Key Program of Natural Science Foundation of Guangdong Province (No. 2017B030311008), and the Fundamental Research Funds for the Central Universities (No. x2jqD2170480).


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Copyright information

© The Natural Computing Applications Forum 2018

Authors and Affiliations

  1. 1.School of Mechanical and Automotive EngineeringSouth China University of TechnologyGuangzhouChina
  2. 2.School of Mechanical and Electrical EngineeringQingdao UniversityQingdaoChina
  3. 3.Department of EngineeringUniversity of MessinaMessinaItaly
  4. 4.School of Mechanical and Automotive EngineeringHubei University of Arts and ScienceXiangyangChina

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