AI-Driven Smart Farming Optimisation in the Green.Dat.AI Data Space
summary
Horizon Europe Green.Dat.AI builds a working pilot that feeds satellite, drone and in‑situ sensors into the GEMMA Fusion Suite and the MyFarm platform to produce NDVI‑based zone maps, shapefiles for tractor onboard import, harvest‑route plans and anomaly alerts; it uses federated learning for privacy‑preserving edge training, digital twins and event detection, reports a 95% energy cut in explainable feature learning plus ~50% model and 42% inference savings, and is live with Slovenian farmers while KPI validation starts.
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chapters (14)
- 0:00Introduction
- 1:03Project goals and data space
- 3:12Energy efficiency focus
- 4:35Smart farming goals and scenarios
- 5:17Fertilization optimization with AI and IoT
- 7:48Harvest timing prediction
- 9:58Anomaly detection in crops
- 13:08My Farm app integration
- 15:21AI services for smart farming
- 17:26Data workflow to insights
- 18:32Gemma Fusion platform
- 19:14AI impact on yield and energy
- 19:56Future innovations
- 21:00Q&A
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