IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v11y2021i2p145-d497096.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/11/2/145/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2077-0472/11/2/145/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Roland W. Scholz, 2016. "Sustainable Digital Environments: What Major Challenges Is Humankind Facing?," Sustainability, MDPI, vol. 8(8), pages 1-31, July.
    2. Maya Gopal P.S. & Bhargavi Renta Chintala, 2020. "Big Data Challenges and Opportunities in Agriculture," International Journal of Agricultural and Environmental Information Systems (IJAEIS), IGI Global, vol. 11(1), pages 48-66, January.
    3. Yang Li & Xuewei Chao, 2020. "ANN-Based Continual Classification in Agriculture," Agriculture, MDPI, vol. 10(5), pages 1-15, May.
    4. Fielke, Simon & Taylor, Bruce & Jakku, Emma, 2020. "Digitalisation of agricultural knowledge and advice networks: A state-of-the-art review," Agricultural Systems, Elsevier, vol. 180(C).
    5. Lioutas, Evagelos D. & Charatsari, Chrysanthi, 2020. "Smart farming and short food supply chains: Are they compatible?," Land Use Policy, Elsevier, vol. 94(C).
    6. Pivoto, Diesson & Barham, Bradford & Dabdab, Paulo & Zhang, Debin & Talamin, Edson, 2019. "Factors influencing the adoption of smart farming by Brazilian grain farmers," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 22(4), April.
    7. Alfons Weersink & Evan Fraser & David Pannell & Emily Duncan & Sarah Rotz, 2018. "Opportunities and Challenges for Big Data in Agricultural and Environmental Analysis," Annual Review of Resource Economics, Annual Reviews, vol. 10(1), pages 19-37, October.
    8. Yingyi Chen & Jing Xu & Huihui Yu & Zhumi Zhen & Daoliang Li, 2016. "Three-Dimensional Short-Term Prediction Model of Dissolved Oxygen Content Based on PSO-BPANN Algorithm Coupled with Kriging Interpolation," Mathematical Problems in Engineering, Hindawi, vol. 2016, pages 1-10, April.
    9. Ali Mostafaeipour & Mohammad Bagher Fakhrzad & Sajad Gharaat & Mehdi Jahangiri & Joshuva Arockia Dhanraj & Shahab S. Band & Alibek Issakhov & Amir Mosavi, 2020. "Machine Learning for Prediction of Energy in Wheat Production," Agriculture, MDPI, vol. 10(11), pages 1-19, October.
    10. Athanasios Balafoutis & Bert Beck & Spyros Fountas & Jurgen Vangeyte & Tamme Van der Wal & Iria Soto & Manuel Gómez-Barbero & Andrew Barnes & Vera Eory, 2017. "Precision Agriculture Technologies Positively Contributing to GHG Emissions Mitigation, Farm Productivity and Economics," Sustainability, MDPI, vol. 9(8), pages 1-28, July.
    11. Chunling Li & Ben Niu, 2020. "Design of smart agriculture based on big data and Internet of things," International Journal of Distributed Sensor Networks, , vol. 16(5), pages 15501477209, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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. 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.
    3. 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.
    4. 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.
    5. 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, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Robert Finger, 2023. "Digital innovations for sustainable and resilient agricultural systems," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 50(4), pages 1277-1309.
    2. Ingram, Julie & Maye, Damian & Bailye, Clive & Barnes, Andrew & Bear, Christopher & Bell, Matthew & Cutress, David & Davies, Lynfa & de Boon, Auvikki & Dinnie, Liz & Gairdner, Julian & Hafferty, Caitl, 2022. "What are the priority research questions for digital agriculture?," Land Use Policy, Elsevier, vol. 114(C).
    3. McGrath, Karen & Brown, Claire & Regan, Áine & Russell, Tomás, 2023. "Investigating narratives and trends in digital agriculture: A scoping study of social and behavioural science studies," Agricultural Systems, Elsevier, vol. 207(C).
    4. Rim Lassoued & Diego M. Macall & Stuart J. Smyth & Peter W. B. Phillips & Hayley Hesseln, 2021. "Expert Insights on the Impacts of, and Potential for, Agricultural Big Data," Sustainability, MDPI, vol. 13(5), pages 1-18, February.
    5. Schnebelin, Éléonore, 2022. "Linking the diversity of ecologisation models to farmers' digital use profiles," Ecological Economics, Elsevier, vol. 196(C).
    6. Rabhi, Loubna & Jabir, Brahim & Falih, Noureddine & Afraites, Lekbir & Bouikhalene, Belaid, 2023. "A Connected farm Metamodeling Using Advanced Information Technologies for an Agriculture 4.0," AGRIS on-line Papers in Economics and Informatics, Czech University of Life Sciences Prague, Faculty of Economics and Management, vol. 15(2), June.
    7. Emily Duncan & Alesandros Glaros & Dennis Z. Ross & Eric Nost, 2021. "New but for whom? Discourses of innovation in precision agriculture," Agriculture and Human Values, Springer;The Agriculture, Food, & Human Values Society (AFHVS), vol. 38(4), pages 1181-1199, December.
    8. Parra-López, Carlos & Reina-Usuga, Liliana & Carmona-Torres, Carmen & Sayadi, Samir & Klerkx, Laurens, 2021. "Digital transformation of the agrifood system: Quantifying the conditioning factors to inform policy planning in the olive sector," Land Use Policy, Elsevier, vol. 108(C).
    9. Lajoie-O'Malley, Alana & Bronson, Kelly & van der Burg, Simone & Klerkx, Laurens, 2020. "The future(s) of digital agriculture and sustainable food systems: An analysis of high-level policy documents," Ecosystem Services, Elsevier, vol. 45(C).
    10. Ancín, María & Pindado, Emilio & Sánchez, Mercedes, 2022. "New trends in the global digital transformation process of the agri-food sector: An exploratory study based on Twitter," Agricultural Systems, Elsevier, vol. 203(C).
    11. Lioutas, Evagelos D. & Charatsari, Chrysanthi & De Rosa, Marcello, 2021. "Digitalization of agriculture: A way to solve the food problem or a trolley dilemma?," Technology in Society, Elsevier, vol. 67(C).
    12. Jennifer Clapp & Sarah-Louise Ruder, 2020. "Precision Technologies for Agriculture: Digital Farming, Gene-EditedCrops, and the Politics of Sustainability," Global Environmental Politics, MIT Press, vol. 20(3), pages 49-69, August.
    13. da Silveira, Franco & da Silva, Sabrina Letícia Couto & Machado, Filipe Molinar & Barbedo, Jayme Garcia Arnal & Amaral, Fernando Gonçalves, 2023. "Farmers' perception of the barriers that hinder the implementation of agriculture 4.0," Agricultural Systems, Elsevier, vol. 208(C).
    14. Ehlers, Melf-Hinrich & Huber, Robert & Finger, Robert, 2021. "Agricultural policy in the era of digitalisation," Food Policy, Elsevier, vol. 100(C).
    15. Sebastian Lieder & Christoph Schröter-Schlaack, 2021. "Smart Farming Technologies in Arable Farming: Towards a Holistic Assessment of Opportunities and Risks," Sustainability, MDPI, vol. 13(12), pages 1-20, June.
    16. Marco Ammoniaci & Simon-Paolo Kartsiotis & Rita Perria & Paolo Storchi, 2021. "State of the Art of Monitoring Technologies and Data Processing for Precision Viticulture," Agriculture, MDPI, vol. 11(3), pages 1-20, February.
    17. Johanna Pfeiffer & Andreas Gabriel & Markus Gandorfer, 2021. "Understanding the public attitudinal acceptance of digital farming technologies: a nationwide survey in Germany," Agriculture and Human Values, Springer;The Agriculture, Food, & Human Values Society (AFHVS), vol. 38(1), pages 107-128, February.
    18. Thomas M. Koutsos & Georgios C. Menexes & Andreas P. Mamolos, 2021. "The Use of Crop Yield Autocorrelation Data as a Sustainable Approach to Adjust Agronomic Inputs," Sustainability, MDPI, vol. 13(4), pages 1-17, February.
    19. Ismael Cristofer Baierle & Francisco Tardelli da Silva & Ricardo Gonçalves de Faria Correa & Jones Luís Schaefer & Matheus Becker Da Costa & Guilherme Brittes Benitez & Elpidio Oscar Benitez Nara, 2022. "Competitiveness of Food Industry in the Era of Digital Transformation towards Agriculture 4.0," Sustainability, MDPI, vol. 14(18), pages 1-22, September.
    20. Basharat Ali & Peter Dahlhaus, 2022. "Roles of Selective Agriculture Practices in Sustainable Agricultural Performance: A Systematic Review," Sustainability, MDPI, vol. 14(6), pages 1-15, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jagris:v:11:y:2021:i:2:p:145-:d:497096. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.