Offline-first AI system for monitoring grain storage conditions and predicting post-harvest deterioration and aflatoxin risk for smallholder farmers in Africa.
# AgriGuard
**Offline-first AI-powered post-harvest grain integrity monitoring and aflatoxin risk mitigation system for smallholder farmers in Africa.**
AgriGuard combines low-cost environmental and grain-moisture sensing, time-series machine learning, and on-device AI to monitor storage conditions, predict grain deterioration risk, and deliver actionable alerts—even in low-connectivity environments.
### Core Focus
* Continuous grain-storage monitoring
* Moisture, temperature, and humidity analysis
* AI-powered deterioration and contamination-risk prediction
* Offline-first, low-resource device deployment
* Time-series modelling and edge AI optimization
* Adaptation to African agricultural and climatic contexts
* Cloud synchronization and continuous model improvement
**Research → Data → Intelligence → Edge Deployment → Field Validation**