Li (2025) A magnetic induction network for high-resolution, real-time soil moisture monitoring in complex subsurface environments

Identification

• Journal: Computers and Electronics in Agriculture
• Year: 2025
• Date: 2025-12-20
• Authors: Zhangyu Li
• DOI: 10.1016/j.compag.2025.111314

Research Groups

• College of Electronics and Information Engineering (School of Robotics), South-Central Minzu University, Wuhan, Hubei Province, China

Short Summary

This study develops and validates a scalable magnetic induction (MI) network for real-time, high-resolution volumetric soil moisture mapping in complex subsurface environments. The system demonstrates a significant reduction in sensing errors and improved accuracy compared to conventional methods, enabling 3D real-time soil moisture imaging.

Objective

• To develop and validate a scalable magnetic induction (MI) network-based sensing system capable of real-time, high-resolution volumetric soil moisture mapping across large and heterogeneous agricultural fields, thereby overcoming the limited coverage and instability of conventional underground sensing technologies.

Study Configuration

• Spatial Scale: Large and heterogeneous agricultural fields, tested over a 40 m range.
• Temporal Scale: Real-time monitoring and imaging.

Methodology and Data

• Models used: COMSOL Multiphysics full-wave simulations, channel frequency response (CFR)-based protocol, multi-frequency phase unwrapping algorithm.
• Data sources: COMSOL Multiphysics full-wave simulations, laboratory testbed experiments.

Main Results

• The developed MI network system reduces average sensing errors by 25–50 % over a 40 m range compared with conventional wireless underground sensing.
• Laboratory testbed experiments confirm a 38 % accuracy improvement over state-of-the-art approaches, achieving a spatial Root Mean Square Error (RMSE) of approximately 0.02 m³/m³.
• The system has the potential to improve irrigation scheduling and enhance water-use efficiency by an estimated 15–25 % in large-scale farming operations.

Contributions

• This work presents the first experimental demonstration of using magnetic induction networking for 3D real-time soil moisture imaging.
• It offers a robust and scalable solution for precision agriculture by enabling distributed, non-invasive subsurface monitoring.
• The system overcomes limitations of conventional sensing technologies regarding spatial coverage, performance in conductive soils, and real-time resolution of heterogeneous moisture patterns.

Funding

• [No specific funding information provided in the text.]

Citation

@article{Li2025magnetic,
  author = {Li, Zhangyu},
  title = {A magnetic induction network for high-resolution, real-time soil moisture monitoring in complex subsurface environments},
  journal = {Computers and Electronics in Agriculture},
  year = {2025},
  doi = {10.1016/j.compag.2025.111314},
  url = {https://doi.org/10.1016/j.compag.2025.111314}
}