Kavuma Chrish
AGRO-SOIL-SMART UGANDA: Harnessing Machine Learning and Remote Sensing for Precision Soil Moisture and Nutrient Mapping
Kavuma Chrish

Methodology

- Stage 1: Data collection (satellite, sensors, climate). - Stage 2: Preprocessing and feature engineering. - Stage 3: Model training (ML and DL algorithms). - Stage 4: Android application development and API integration. - Stage 5: Validation using RMSE, ubRMSE, Bias error, and Pearson correlation. - Duration: 1 year.