Chinese Journal of Intelligent Science and Technology ›› 2022, Vol. 4 ›› Issue (2): 288-297.doi: 10.11959/j.issn.2096-6652.202231

• Papers and Reports • Previous Articles    

Distributed agricultural organization based on federated learning

Mengzhen KANG1,2, Xiujuan WANG1,3, Dong LI4, Xuwei WANG5, Haoyu WANG1,6, Menghan FAN1,2, Yulin XU1,2, Fei-Yue WANG1,2   

  1. 1 The State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
    2 School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
    3 Beijing Engineering Research Center of Intelligent Systems and Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
    4 Institute of Digital Agriculture, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, China
    5 Ningbo Agricultural Technology Extension Station, Ningbo 315012, China
    6 Qingdao AgriTech Company, Ltd., Qingdao 266000, China
  • Online:2022-06-01 Published:2022-06-01
  • Supported by:
    The National Key Research and Development Program of China(2021ZD0113704);The National Natural Science Foundation of China(62076239);Chinese Academy of Sciences-Thailand National Science and Technology Development Agency Joint Research Program(GJHZ2076);The Strategic Priority Research Program of the Chinese Academy of Sciences(XDA20030102)


At present, small-scale agriculture is dominating in China.How to develop appropriate smart agriculture for agricultural management with small farmers and small plots is quite challenging.A distributed agricultural AI framework combining federal learning and blockchain technology was proposed, which can achieve the purpose of the training model and establish the incentive mechanism for participants without data sharing.This framework helped make full use of agricultural multi-source heterogeneous data, reducing user data requirements, developing decision-making models according to local conditions, and promoting the connection of production and marketing of small-scale agriculture.

Key words: federated intelligence, agricultural big data, decision support, block-chain technology, agricultural management system

CLC Number: 

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