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This document presents a novel framework utilizing Ground Penetrating Radar (GPR) and machine learning to enhance soil moisture assessment in precision agriculture, particularly for mega farms. The approach involves generating a synthetic dataset with gprMax, validating it against real-world data, and employing feature engineering to optimize machine learning models for accurate predictions. The proposed method aims to improve irrigation practices and resource management, contributing to sustainable agricul

Author

J. JENCEWIN MCA

Language

EN