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From Smart Farming towards Unmanned Farms: A New Mode of Agricultural Production

Author

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  • Tan Wang

    (National Innovation Center for Digital Fishery, China Agricultural University, Beijing 100083, China
    Beijing Engineering and Technology Research Centre for Internet of Things in Agriculture, Beijing 100083, China
    Key Laboratory of Agricultural Information Acquisition Technology, Ministry of Agriculture, Beijing 100083, China
    College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China)

  • Xianbao Xu

    (National Innovation Center for Digital Fishery, China Agricultural University, Beijing 100083, China
    Beijing Engineering and Technology Research Centre for Internet of Things in Agriculture, Beijing 100083, China
    Key Laboratory of Agricultural Information Acquisition Technology, Ministry of Agriculture, Beijing 100083, China
    College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China)

  • Cong Wang

    (National Innovation Center for Digital Fishery, China Agricultural University, Beijing 100083, China
    Beijing Engineering and Technology Research Centre for Internet of Things in Agriculture, Beijing 100083, China
    Key Laboratory of Agricultural Information Acquisition Technology, Ministry of Agriculture, Beijing 100083, China
    College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China)

  • Zhen Li

    (National Innovation Center for Digital Fishery, China Agricultural University, Beijing 100083, China
    Beijing Engineering and Technology Research Centre for Internet of Things in Agriculture, Beijing 100083, China
    Key Laboratory of Agricultural Information Acquisition Technology, Ministry of Agriculture, Beijing 100083, China
    College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China)

  • Daoliang Li

    (National Innovation Center for Digital Fishery, China Agricultural University, Beijing 100083, China
    Beijing Engineering and Technology Research Centre for Internet of Things in Agriculture, Beijing 100083, China
    Key Laboratory of Agricultural Information Acquisition Technology, Ministry of Agriculture, Beijing 100083, China
    College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China)

Abstract

Agriculture is the most important industry for human survival and solving the hunger problem worldwide. With the growth of the global population, the demand for food is increasing, which needs more agriculture labor. However, the number of people willing to engage in agricultural work is decreasing, causing a severe shortage of agricultural labor. Therefore, it is necessary to study the mode of agricultural production without labor force participation. With the rapid development of the Internet of Things, Big Data, artificial intelligence, robotics and fifth-generation (5G) communication technology, robots can replace humans in agricultural operations, thus enabling the establishment of unmanned farms in the near future. In this review, we have defined unmanned farms, introduced the framework of unmanned farms, analyzed the current state of the technology and how these technologies can be used in unmanned farms, and finally discuss all the technical challenges. We believe that this review will provide guidance for the development of unmanned farms and provide ideas for further investigation of these farms.

Suggested Citation

  • Tan Wang & Xianbao Xu & Cong Wang & Zhen Li & Daoliang Li, 2021. "From Smart Farming towards Unmanned Farms: A New Mode of Agricultural Production," Agriculture, MDPI, vol. 11(2), pages 1-26, February.
    • Handle: RePEc:gam:jagris:v:11:y:2021:i:2:p:145-:d:497096
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    References listed on IDEAS

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    Cited by:

    1. Akshat Jain & Prateek Jain, 2022. "Advances in Sustainable Agri Business Paradigm: Developing an Innovative Business and Marketing Model to abridge human labour predicting Neural Behaviour," The Indian Journal of Labour Economics, Springer;The Indian Society of Labour Economics (ISLE), vol. 65(4), pages 1193-1208, December.
    2. Haoling Ren & Jiangdong Wu & Tianliang Lin & Yu Yao & Chang Liu, 2023. "Research on an Intelligent Agricultural Machinery Unmanned Driving System," Agriculture, MDPI, vol. 13(10), pages 1-19, September.
    3. Bin Zhang & Xuegeng Chen & Huiming Zhang & Congju Shen & Wei Fu, 2022. "Design and Performance Test of a Jujube Pruning Manipulator," Agriculture, MDPI, vol. 12(4), pages 1-21, April.
    4. Juan D. Borrero & Jesús Mariscal, 2022. "A Case Study of a Digital Data Platform for the Agricultural Sector: A Valuable Decision Support System for Small Farmers," Agriculture, MDPI, vol. 12(6), pages 1-15, May.
    5. Yehong Liu & Xin Wang & Dong Dai & Can Tang & Xu Mao & Du Chen & Yawei Zhang & Shumao Wang, 2023. "Knowledge Discovery and Diagnosis Using Temporal-Association-Rule-Mining-Based Approach for Threshing Cylinder Blockage," Agriculture, MDPI, vol. 13(7), pages 1-21, June.

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