Measurement-Based Model for Water Content Estimation in Sustainable Granular Materials Using an IoT Custom Device

Soil water content (SWC) has a primary importance in several scientific fields involving the geotechnical, hydrological agronomic, ecological, and biological properties of the soil mass. In recent years, several techniques for determining SWC in the laboratory and situ have been proposed and developed. Applying these techniques and adopted measurement systems to different soil types is widely discussed in the literature, thus highlighting a nontrivial issue deserving further experimental research. This article presents the results of applying a capacitive sensor originally developed for SWC measurement to sustainable granular materials. In particular, the application regards coffee ground samples with two grain size distributions prepared dry and at increasing gravimetric water content (GWC) at different initial void ratios. This article presents a measurement-based analytical model for estimating the water content using low-cost low-frequency Internet of Things (IoT) sensors. The proposed model estimates the water content exploiting both capacitance and conductance measurements of the parallel electrical model. The obtained results show that including conductance measurements improves the water content estimation with respect to using capacitance measurements only.