"Treating the Earth like a living organism. Monitoring, diagnosing, and healing it with AI."
GaiaAir is an open-science initiative designed to bridge the gap between complex satellite telemetry and human-actionable insights. By combining Satellite Imagery Analysis with Cohere's Multilingual Language Models, we aim to create an "Earth Doctor" that not only detects environmental anomalies (droughts, pollution, crop stress) but explains them to local communities in their native languages.
The system operates on a "Neural-Symbolic" pipeline:
- Sensory Layer (Vision): Ingests data from Sentinel-2, Landsat, and ground IoT sensors.
- Reasoning Layer (Cohere Command R+): Interprets structured data to generate advisory reports.
- Retrieval Layer (Cohere Embed + Rerank): Contextualizes alerts using a vector database of UN Climate Reports and agricultural best practices.
- FarmVital: Multilingual SMS/WhatsApp advisory for farmers based on micro-climate data.
- GaiaSense: Real-time anomaly detection for climate events.
- RAG-based Policy Engine: Searchable climate intelligence for policymakers.
- AI/LLM: Cohere Command R+, Cohere Embed v3.0, LangChain.
- Data: Streamlit (Dashboard), Python, GeoPandas.
- Infrastructure: Google Earth Engine API.
This project is currently in the Research Phase. We welcome contributions from data scientists and climate researchers. Please open an issue to discuss potential collaborations.
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