Indirect Measurement of Soil Volumetric Water Content Using Deep Learning Enhanced by Wind Speed Factor

Using LoRa-RSSI data of underground Internet of Things (UIoT) combined with deep learning to achieve volumetric water content (VWC) indirectly is crucial for agriculture, industry, forestry, environmental monitoring and so on. This paper introduces a method that incorporates wind speed factor to enhance the accuracy of this measurement approach. Through field experiments, the feasibility and effectiveness of this method have been verified. Characterized by simple implementation, low cost, and excellent performance, this method is expected to provide an effective indirect measurement solution for relevant fields.