Harnessing AI & Remote Sensing for Climate-Resilient Agriculture in Somalia

Agricultural productivity in East Africa is increasingly challenged by climate variability, erratic rainfall, and pest outbreaks. At Sabuul, our digital innovation team is leveraging satellite remote sensing combined with machine learning algorithms to monitor crop health in real-time. By integrating multispectral imaging with ground-level weather data, the Sabuul v1.0 platform can detect plant stress weeks before visible symptoms appear. This allows smallholder farmers to apply targeted interventions, saving crops and minimizing resource waste. Our recent field trials in Lower Shabelle demonstrated a 30% reduction in crop loss caused by Fall Armyworm when AI diagnostic advisory was delivered to registered farming cooperatives early in the season.