Uruguay Climate Change Monitoring & AI Analysis System
Inspiration
Uruguay's agriculture is vulnerable. We bridge the gap between complex climate data and actionable, predictive policy using Gemini AI and Cyoda protocols.
What it does
Transforms 60 years of climate data with LSTM forecasting and anomaly detection. Gemini AI provides plain-language, actionable policy insights via a React dashboard.
How we built it
Flask/React architecture, containerized via Docker, integrates four distinct ML models. Custom Gemini prompt engineering and Cyoda MCP manage enterprise alerts automatically.
Challenges we ran into
Handling missing time-series data and multi-framework ML integration were tough. We overcame unreliable outputs via strict Gemini prompt engineering and Docker orchestration.
Accomplishments that we're proud of
We integrated four ML models and created genuinely useful Gemini AI insights. Proud of our production-ready Docker deployment and automated Cyoda enterprise alerting.
What we learned
Ensemble ML models are robust. Prompt engineering is critical for structured AI outputs. Standardized protocols (Cyoda MCP) are essential for enterprise AI integration.
What's next for Uruguay climate change challenge
Expand to real-time data and Graph Neural Networks. Deepen Gemini integration, develop mobile apps, and secure partnerships for regional impact.
Log in or sign up for Devpost to join the conversation.