Introduction

Agricultural productivity in Uganda is constrained by poor soil moisture and nutrient management, leading to food insecurity and reduced yields. Conventional soil assessment methods are slow, labor-intensive, and often inaccurate. This project proposes the development of an Android-based system that integrates machine learning algorithms, remote sensing data, and ground-based sensors to generate real-time soil moisture and nutrient maps. The innovation will empower farmers, extension agents, and policymakers with actionable insights for precision agriculture, aligning with SDGs 2 (Zero Hunger) and 15 (Life on Land).