Passive ultra-high-frequency (UHF) radio-frequency identification (RFID) systems provide a battery-free platform for soil moisture sensing; however, their performance is strongly influenced by moisture-dependent dielectric loading of the surrounding soil. Existing RFID-based sensing approaches are largely empirical and do not establish a predictive relationship between soil dielectric properties and antenna electromagnetic response. This paper presents an integrated soil–RFID electromagnetic interaction model that links volumetric soil moisture content (θ) to antenna resonant frequency and input impedance through dielectric representation and full-wave electromagnetic simulation. Soil dielectric properties are modelled as complex permittivity and incorporated into electromagnetic simulations of a passive UHF RFID tag embedded in sand, loam, and clay soils over a moisture range of 0–20%. The results show a monotonic decrease in resonant frequency with increasing moisture, with sensitivities ranging from −30 to −38 MHz/% depending on soil type. Input impedance variation and radiation efficiency degradation are observed due to increased dielectric loss, resulting in gain reduction of up to 4–6 dB under high moisture conditions. A dual-mode resonance tracking approach is implemented to maintain continuous frequency extraction across the full moisture range. Analytical models describing the dependence of resonant frequency and impedance on soil moisture demonstrate strong agreement with simulation data, with coefficient of determination 〖 (R〗²), ranging from 0. 92 to 0. 97 and low root mean square errors across all parameters. The proposed model provides a predictive framework for analysing soil–antenna interaction and enables reliable RFID-based soil moisture sensing without reliance on empirical calibration.
Richard-John et al. (Fri,) studied this question.