Simulation Study of Surface Acoustic Wave Sensors for Soil Parameter Monitoring

Soil parameters such as moisture, pH, and salinity are essential for agricultural productivity and environmental management. However, traditional monitoring methods, while accurate, are time-consuming and lack real-time capabilities, limiting their suitability for precision agriculture. Surface acoustic wave (SAW) sensors offer a promising alternative due to their high sensitivity, robustness, and real-time monitoring capabilities. In this study, a SAW sensor was designed and simulated using COMSOL Multiphysics to detect soil moisture. The sensor design employs a lithium tantalate piezoelectric substrate and interdigitated transducers (IDTs), with graphene oxide (GO) as a functional coating to enhance sensitivity. Simulation results showed that at a GO coating thickness of 350 nm, the sensor achieved the highest frequency shift at 70% relative humidity, demonstrating optimal sensitivity. Additionally, dynamic response analysis revealed that as humidity increased from 0% to 100%, the response time grew nonlinearly from 2.5 seconds to 42.2 seconds. The simulation results of the nonlinear growth trend of the optimal coating thickness and response time provide a clear direction for practical humidity sensor design optimization, dynamic environmental adaptation analysis, and future experimental validation and development. This study provides a theoretical foundation for the development of SAW-based soil sensors and outlines future directions for expanding functionality to monitor pH and salinity. Future work will focus on transitioning to 3D FEM models, experimental validation, and advanced material development. Fabricating actual sensors and validating simulations with experimental data will ensure reliability, supporting the broader application of SAW sensors in precision agriculture and environmental management.