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Journal of library and information science in agriculture ›› 2019, Vol. 31 ›› Issue (4): 4-18.doi: 10.13998/j.cnki.issn1002-1248.2019.04.19-0150

• Special review •     Next Articles

Cognitive Computing and Applications in Agriculture

WANG Ting1,2, CUI Yunpeng1,2, WANG Jian1,2, LIU Tingting1,2, WANG Mo1,2   

  1. 1.Information Institute of Agriculture, Chinese Academy of Agricultural Sciences, Beijing 100081, China;
    2.Key Laboratory of Big Agri-data, Ministry of agriculture and rural areas, Beijing 100081, China
  • Received:2019-03-06 Online:2019-04-05 Published:2019-06-21

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Abstract: Cognitive computing is a nascent interdisciplinary domain, and it is also an evolution of technology that attempts to make sense of a complex world that is drowning in data in all forms and shapes. It is a confluence of cognitive science, neuroscience, date science, and cloud computing, which makes cognitive computing powerful and has the potential for groundbreaking discoveries and advances. We are entering a new era in cognitive computing that will transform the way humans collaborate with machines to gain actionable insights in areas such as healthcare, manufacturing, transportation, retail, retail, and financial services. Served as a catalyst for advancing research in cognitive computing, a coherent body of knowledge and recent research in cognitive computing are brought together. First, a deep look was taken at the concept of cognitive computing and an interdisciplinary introduction to cognitive computing, which was to provide a unified view of the discipline. Second, the development procedure was provided. Thirdly, overview of three major categories of cognitive architectures and principal technologies and approaches that are fundamental to a cognitive system were demonstrated. Some of the industries that were early adopters of cognitive com-puting and the types of solutions that were being created were also included. Finally, the applications of cognitive computing in agricultural area was discussed. It covered the applications, the system, the future and its challenges. Cognitive systems can help with the transfer of knowledge and best practices in agricultural area, and using cognitive computing to help decision support services has huge potential. In these use cases, a cognitive system is designed to build a dialog between human and machine so that best practices are learned by the system as opposed to being programmed as a set of rules. It is clear that cognitive computing is in its early stages of maturation. The list of potential uses of a cognitive computing approach will continue to grow over time, and the coming decade will bring many new software and hardware innovations to stretch the limits of what is possible.

Key words: cognitive computing, cognitive system, agricultural cognitive system, artificial intelligence

CLC Number: 

  • G202
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