Deployment-Oriented Evaluation of Passive UHF RFID Soil Moisture Sensing Using System-Level Simulation and Link-Budget Analysis

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@article{1715763,
      author = {Pauline O Richard-John, Nkolika O. Nwazor, M., Ehikhamenle},
      title = {Deployment-Oriented Evaluation of Passive UHF RFID Soil Moisture Sensing Using System-Level Simulation and Link-Budget Analysis},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {9},
      number = {9},
      pages = {3296-3306},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1715763.pdf},
      abstract = {Passive ultra-high-frequency (UHF) radio-frequency identification (RFID) technology offers a scalable, battery-free solution for distributed soil moisture sensing in precision agriculture and environmental monitoring. However, the deployment performance of RFID systems in soil environments is strongly constrained by moisture-dependent electromagnetic losses, which are often not quantified at the system level. This study presents a deployment-oriented evaluation framework that links electromagnetic antenna behaviour to practical RFID performance metrics using system-level simulation and link-budget analysis. A previously developed passive UHF RFID tag antenna was evaluated under soil-embedded conditions across a volumetric moisture range of 0–20% for representative soil textures, including sand, loam, and clay. Electromagnetic simulation outputs—resonant frequency, radiation efficiency, and realized antenna gain—were used as inputs to estimate maximum read range and received signal strength indicator (RSSI). Environmental robustness was further assessed through temperature and salinity variation, while manufacturing variability was analysed using Monte Carlo simulation. Results demonstrate that increasing soil moisture significantly degrades system performance. The maximum read range decreases from approximately 20–22 m under dry conditions to 7–12 m at 20% moisture, representing a reduction exceeding 50–65%. Similarly, RSSI values decrease from approximately −55 to −57 dBm under dry conditions to approximately −67 to −71 dBm at 20% moisture, corresponding to a reduction of approximately 12–16 dB, depending on soil type. Clay soils exhibit the most severe degradation due to higher permittivity and conductivity. Temperature effects are comparatively minor, while increased salinity introduces additional attenuation and further reduces system performance. Monte Carlo analysis confirms that the moisture-dependent sensing behaviour remains robust under realistic fabrication tolerances. The proposed framework provides a physically grounded and scalable approach for evaluating deployment feasibility of passive UHF RFID soil moisture sensing systems. The results offer quantitative design guidelines for optimizing tag placement, reader configuration, and operational limits, enabling reliable implementation of battery-free sensing solutions in real-world agricultural environments.},
      keywords = {Passive UHF RFID; Soil moisture sensing; Link-budget analysis; Read range; RSSI; Backscatter communication; Electromagnetic modelling; Deployment evaluation; Precision agriculture; Environmental sensing},
      month = {March},
      doi = {https://doi.org/10.64388/IREV9I9-1715763}
  }