This document presents a system that uses IoT and machine learning techniques to detect crop health through data collected by UAVs. The system was able to detect crop health with various machine learning models and evaluate performance metrics like recall, precision and f-measure. However, accurately detecting crop health remains challenging and depends on additional crop and environmental factors. Future work aims to improve data sharing and analysis of more detailed metrics to better generate recommendations.