RFID-Based Real-Time Salt Concentration Monitoring with Adaptive EKF

Salt concentration monitoring is crucial for industrial process control and wastewater management, yet existing methods often lack real-time capability or require invasive sampling. This paper presents a novel RFID wireless sensing system for noninvasive solution concentration monitoring, combining physical modeling with advanced estimation algorithms. By combining the Cole-Cole model and the slit cylindrical capacitor (SCC) model, the system establishes physics-based state-space models to characterize concentration-dependent RFID signal variations. The concentration dynamics are modeled as a hidden Markov process and tracked using an adaptive extended Kalman filter (AEKF). The AEKF algorithm avoids computationally expensive inversion of complex observation equations while automatically adjusting noise covariance matrices via innovation sequence. Experimental results demonstrate a mean relative error (MRE) of 2.8% for CaCl₂ solution across 2-10 g/L concentrations. Within the experimentally validated optimal range (2-8 g/L CaCl₂), the system maintains MRE below 3% under artificially introduced measurement noise, confirming its strong robustness. Compared with baseline approaches, the proposed AEKF algorithm shows improved performance in both accuracy and computational efficiency.