IDEAS home Printed from https://ideas.repec.org/a/sae/intdis/v16y2020i5p1550147720917065.html

Design of smart agriculture based on big data and Internet of things

Author

Listed:
  • Chunling Li
  • Ben Niu

Abstract

With the wide application of Internet of things technology and era of large data in agriculture, smart agricultural design based on Internet of things technology can efficiently realize the function of real-time data communication and information processing and improve the development of smart agriculture. In the process of analyzing and processing a large amount of planting and environmental data, how to extract effective information from these massive agricultural data, that is, how to analyze and mine the needs of these large amounts of data, is a pressing problem to be solved. According to the needs of agricultural owners, this article studies and optimizes the data storage, data processing, and data mining of large data generated in the agricultural production process, and it uses the k-means algorithm based on the maximum distance to study the data mining. The crop growth curve is simulated and compared with improved K-means algorithm and the original k-means algorithm in the experimental analysis. The experimental results show that the improved K-means clustering method has an average reduction of 0.23 s in total time and an average increase of 7.67% in the F metric value. The algorithm in this article can realize the functions of real-time data communication and information processing more efficiently, and has a significant role in promoting agricultural informatization and improving the level of agricultural modernization.

Suggested Citation

  • 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.
    • Handle: RePEc:sae:intdis:v:16:y:2020:i:5:p:1550147720917065
    DOI: 10.1177/1550147720917065
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/1550147720917065
    Download Restriction: no
    File URL: https://libkey.io/10.1177/1550147720917065?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Wolfert, Sjaak & Ge, Lan & Verdouw, Cor & Bogaardt, Marc-Jeroen, 2017. "Big Data in Smart Farming – A review," Agricultural Systems, Elsevier, vol. 153(C), pages 69-80.
    2. Protopop, Iuliia & Shanoyan, Aleksan, . "Big Data and Smallholder Farmers: Big Data Applications in the Agri-Food Supply Chain in Developing Countries," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 19(A), pages 1-18.
    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. Huo, Dongyang & Malik, Asad Waqar & Ravana, Sri Devi & Rahman, Anis Ur & Ahmedy, Ismail, 2024. "Mapping smart farming: Addressing agricultural challenges in data-driven era," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).
    2. Zitian Fu & Shunyu Yao & Reza Farzipoor Saen & Kaiyang Zhong & Yan Liu, 2025. "Impact of digital transformation on agricultural ecological efficiency: empirical findings from China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 27(4), pages 8557-8595, April.
    3. repec:ags:aolpei:338008 is not listed on IDEAS
    4. Ammad-ul-Islam, 2024. "IoTin Developing the Smart Farming and Agricultural Technologies," International Journal of Innovations in Science & Technology, 50sea, vol. 6(4), pages 1621-1634, October.
    5. 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.
    6. Yu Sun & Zhe Zhao & Mingquan Li, 2022. "Coordination of agricultural informatization and agricultural economy development: A panel data analysis from Shandong Province, China," PLOS ONE, Public Library of Science, vol. 17(9), pages 1-20, September.
    7. 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.
    8. Rajasekhar Chaganti & Vijayakumar Varadarajan & Venkata Subbarao Gorantla & Thippa Reddy Gadekallu & Vinayakumar Ravi, 2022. "Blockchain-Based Cloud-Enabled Security Monitoring Using Internet of Things in Smart Agriculture," Future Internet, MDPI, vol. 14(9), pages 1-20, August.

    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. Lin Xie & Biliang Luo & Wenjing Zhong, 2021. "How Are Smallholder Farmers Involved in Digital Agriculture in Developing Countries: A Case Study from China," Land, MDPI, vol. 10(3), pages 1-16, March.
    2. Oliver Falck & Johannes Koenen, 2020. "Rohstoff „Daten“: Volkswirtschaflicher Nutzen von Datenbereitstellung – eine Bestandsaufnahme," ifo Forschungsberichte, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 113.
    3. Hrosul, Viktoriia & Kruhlova, Olena & Kolesnyk, Alina, 2023. "Digitalization of the agricultural sector: the impact of ICT on the development of enterprises in Ukraine," Agricultural and Resource Economics: International Scientific E-Journal, Agricultural and Resource Economics: International Scientific E-Journal, vol. 9(4), December.
    4. Ascui, Francisco & Ball, Alex & Kahn, Lewis & Rowe, James, 2021. "Is operationalising natural capital risk assessment practicable?," Ecosystem Services, Elsevier, vol. 52(C).
    5. Huo, Dongyang & Malik, Asad Waqar & Ravana, Sri Devi & Rahman, Anis Ur & Ahmedy, Ismail, 2024. "Mapping smart farming: Addressing agricultural challenges in data-driven era," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).
    6. Pigford, Ashlee-Ann E. & Hickey, Gordon M. & Klerkx, Laurens, 2018. "Beyond agricultural innovation systems? Exploring an agricultural innovation ecosystems approach for niche design and development in sustainability transitions," Agricultural Systems, Elsevier, vol. 164(C), pages 116-121.
    7. Tianyu Qin & Lijun Wang & Yanxin Zhou & Liyue Guo & Gaoming Jiang & Lei Zhang, 2022. "Digital Technology-and-Services-Driven Sustainable Transformation of Agriculture: Cases of China and the EU," Agriculture, MDPI, vol. 12(2), pages 1-16, February.
    8. Viet, Nguyen Quoc & Behdani, Behzad & Bloemhof, Jacqueline, . "Value of Information to Improve Daily Operations in High-Density Logistics," International Journal on Food System Dynamics, International Center for Management, Communication, and Research, vol. 9(01).
    9. repec:ags:areint:342110 is not listed on IDEAS
    10. 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.
    11. Li, Lei & Lin, Jiabao & Ouyang, Ye & Luo, Xin (Robert), 2022. "Evaluating the impact of big data analytics usage on the decision-making quality of organizations," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    12. Tran, Duc Thanh & Dieu Duong, My Thi & Hoang, Hung Gia, 2025. "Perception and factors affecting farmers’ adoption of smart agriculture in Vietnam: Implications for extension strategies," World Development Perspectives, Elsevier, vol. 38(C).
    13. Panos Constantinides & Ola Henfridsson & Geoffrey G. Parker, 2018. "Introduction—Platforms and Infrastructures in the Digital Age," Information Systems Research, INFORMS, vol. 29(2), pages 381-400, June.
    14. Iban, Muzaffer Can & Aksu, Oktay, 2020. "A model for big spatial rural data infrastructure in Turkey: Sensor-driven and integrative approach," Land Use Policy, Elsevier, vol. 91(C).
    15. Ayanwale, Adeolu & Kehinde, Ayodeji D., 2025. "Determinants of use of digital innovation and its impact on land acquisition and food security among farming households in Nigeria," World Development Perspectives, Elsevier, vol. 39(C).
    16. Biswajit Lahiri & Ram Kumar Kurmi & Soibam Khogen Singh & Amitava Ghosh & Prasenjit Pal & Sannappa Thippeswamy Pavan Kumar & Chandrasekhar Nirmalkar & Anamika Debnath, 2025. "Determinants of Digitised Farm Information Outreach in Aquaculture: A Case of Mobile Phone Application for Smallholder Fish Farmers in North East India," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 16(4), pages 15342-15380, October.
    17. Divya Suresh & Abhishek Choudhury & Yinjia Zhang & Zhiying Zhao & Rajib Shaw, 2024. "The Role of Data-Driven Agritech Startups—The Case of India and Japan," Sustainability, MDPI, vol. 16(11), pages 1-17, May.
    18. Fengwan Zhang & Xueling Bao & Xin Deng & Dingde Xu, 2022. "Rural Land Transfer in the Information Age: Can Internet Use Affect Farmers’ Land Transfer-In?," Land, MDPI, vol. 11(10), pages 1-14, October.
    19. Simon Marvin & Lauren Rickards & Jonathan Rutherford, 2024. "The urbanisation of controlled environment agriculture: Why does it matter for urban studies?," Urban Studies, Urban Studies Journal Limited, vol. 61(8), pages 1430-1450, June.
    20. Alexander McBratney & Minhyung Park, 2025. "Agriculture over the Horizon: A Synthesis for the Mid-21st Century," Sustainability, MDPI, vol. 17(21), pages 1-20, October.
    21. Li, Rongda & He, Jing, 2024. "FinTech development and household resilience to negative income shocks: The role of informal risk sharing," International Review of Economics & Finance, Elsevier, vol. 94(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:sae:intdis:v:16:y:2020:i:5:p:1550147720917065. 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: SAGE Publications (email available below). General contact details of provider: .

    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.