Comparison of Calibration Strategies for a High Sensitivity PEI-Based RF Humidity Sensor

In this study, a radio frequency (RF) humidity sensor for monitoring outdoor relative humidity (RH) was developed using polyethyleneimine as a sensing material. The sensor’s performance was assessed in laboratory and outdoor conditions. The primary sensor demonstrated an exponential sensitivity in frequency and magnitude, approximately −3.65 MHz/%RH and −7.69 MHz/%RH, −0.051 dB/%RH, and −0.12 dB/%RH, across the RH ranges of 30%RH−50%RH and 50%RH−70%RH, respectively, with consistent results from 25 °C to 45 °C. The sensor exhibited a response and recovery time of 22/44 s, with minimal hysteresis and marginal cross-sensitivity to temperature. Following calibration using different calibration methods (analytical and machine-learning-based techniques), the RH prediction performance was gauged on a separate dataset. The exponential calibration law achieved mean absolute errors (MAEs) as low as 0.8%RH, while other methods, such as Gaussian regression process, k-nearest neighbor (KNN), and generalized linear regression (GLR), resulted in MAE of 0.9%RH, 1%RH, and 1.1%RH. A secondary sensor, also exhibiting exponential sensitivity, underwent initial laboratory testing before transitioning to outdoor conditions. Applying laboratory calibration to outdoor data resulted in an MAE of 4.4%RH, showing remarkable transferability with only 0.8%RH increased MAE. Cross-sensitivity analysis revealed no dependency with temperature, NO2, NO, CO, CO2, and O3 in outdoor conditions. Finally, we confirmed the transferability of calibration between the two sensors under laboratory and outdoor conditions, utilizing output standardization with the slope-bias correction algorithm. This research underscores the potential of our RF humidity sensor for accurate outdoor RH monitoring.