Smart Farming: Dual-Mode Soil Sensor for High-Precision Moisture and Salinity Estimation Using Frequency- and Time-Domain Analysis

Abstract

Accurate and simultaneous measurement of soil moisture and salinity remains a significant challenge in precision agriculture, as most existing sensors are designed to measure only one parameter or suffer from reduced accuracy under varying soil conditions. This limitation affects irrigation management, crop productivity, and long-term soil health monitoring. This article presents a compact electronic sensing system for simultaneous monitoring of soil moisture and salinity, designed for precision agriculture, and intelligent irrigation management. The proposed sensor integrates dual-domain sensing within a unified electronic architecture, combining time-domain signal analysis with wideband frequency-domain measurements to improve parameter discrimination and measurement reliability. In the time-domain mode, a continuous-wave excitation signal is processed through an analog phase and magnitude detection circuit to extract phase difference ($\Delta \varphi $) and magnitude ratio, which are sensitive to changes in the dielectric properties of soil. In the frequency-domain mode, the system performs broadband analysis from 50 to 300 MHz to identify null-frequency shift ($\Delta f$) and null-depth, enabling enhanced sensitivity to salinity-induced conductivity variations. A lightweight machine-learning model is implemented for real-time mapping of the extracted electronic sensing features to volumetric water content (VWC) and soil salinity levels, enabling calibration-free operation across different soil conditions. Experimental validation using soil samples with varying moisture and salinity concentrations demonstrates high measurement accuracy, achieving a mean squared error of 1.5% for VWC estimation and below 2.8% for salinity prediction.