About This Project

Deploy IoT sensor networks integrated with machine learning to optimize temperature, humidity, and gas composition throughout post-harvest supply chains. System predicts spoilage 48 hours in advance, enabling dynamic routing to nearest markets. Reduces post-harvest losses by 60-75% while improving farmer incomes by 35-45%. Cost-effective implementation using recycled refrigeration equipment and local technician training networks across 12 African countries.

Timeline