IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v15y2025i5p467-d1596976.html
   My bibliography  Save this article

Design and Experiment of an Internet of Things-Based Wireless System for Farmland Soil Information Monitoring

Author

Listed:
  • Guanting Ou

    (College of Engineering, South China Agricultural University, Guangzhou 510642, China)

  • Yu Chen

    (College of Engineering, South China Agricultural University, Guangzhou 510642, China)

  • Yunlei Han

    (China Association of Agricultural Science Societies, Beijing 100000, China)

  • Yunuo Sun

    (College of Engineering, South China Agricultural University, Guangzhou 510642, China)

  • Shunan Zheng

    (Rural Energy and Environment Agency, Ministry of Agriculture and Rural Affairs, Beijing 100000, China)

  • Ruijun Ma

    (College of Engineering, South China Agricultural University, Guangzhou 510642, China)

Abstract

Soil environmental monitoring is crucial for ensuring the sustainability and productivity of agriculture. This study aims to develop a wireless soil monitoring system that utilizes Narrowband Internet of Things (NB-IoT), solar energy, and Global Positioning System (GPS) technologies to address the issues of high labor demand, high costs, and delayed feedback in traditional soil monitoring methods. This system can collect soil temperature, humidity, and meteorological data in real time, transmit them to a cloud platform for analysis and visualization, and predict future soil data. It employs multiple learning algorithms to build models and uses the Tree-structured Parzen Estimator (TPE) algorithm for hyperparameter optimization. Field stability experiments were conducted on the system, and the performance of the soil moisture prediction model was evaluated. During the 84-day stability experiment, the system operated stably for 80 days, with a data collection success rate of 95.87%. In the performance evaluation of the soil moisture model, the GBDT model achieved a coefficient of determination (R²) of 0.9838 on the validation set and a root-mean-square error (RMSE) of 0.0013, with an RMSE of 0.0013 on the test set as well. The experimental results demonstrate that the system is stable and reliable, featuring low power consumption, wide coverage, and high accuracy. It can effectively predict soil moisture, providing timely and accurate support for irrigation and farming decisions.

Suggested Citation

  • Guanting Ou & Yu Chen & Yunlei Han & Yunuo Sun & Shunan Zheng & Ruijun Ma, 2025. "Design and Experiment of an Internet of Things-Based Wireless System for Farmland Soil Information Monitoring," Agriculture, MDPI, vol. 15(5), pages 1-24, February.
    • Handle: RePEc:gam:jagris:v:15:y:2025:i:5:p:467-:d:1596976
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/15/5/467/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2077-0472/15/5/467/
    Download Restriction: no
    ---><---

    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:15:y:2025:i:5:p:467-:d:1596976. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.