Seminario Smart Sensing and AI for Precision Irrigation

The seminar will be held by Alahmad Tarek, from the Department of Bioengineering and Precision Technology, University of Gyor (Hungary).

This seminar introduces a data-driven framework for soil moisture monitoring and prediction in agricultural systems, combining IoT-based field sensing with satellite remote sensing and machine learning. The presentation covers how meteorological data collected through IoT sensor networks and vegetation indices derived from Sentinel-2 imagery can be integrated to predict soil moisture content at multiple depths across contrasting soil types/textures. Key findings from a series of published studies are presented, highlighting how depth-specific and soil-type-specific machine learning models outperform generalized approaches, and how explainable AI techniques specifically SHAP analysis help identify the dominant environmental drivers of soil moisture variability at different soil layers. The seminar concludes by discussing how these model outputs can be translated into practical irrigation management recommendations, contributing to more efficient and sustainable use of water resources in modern crop systems.