GreenNeural generates real‑time climate risk scores using live environmental data from trusted global sources. For each selected city, the system performs three steps:

1. Live Environmental Data Fetching: We retrieve real‑time weather and air‑quality measurements using the OpenWeather API, including temperature, humidity, rainfall, and PM2.5 pollution levels.
2. Risk Scoring Engine: GreenNeural applies a transparent, rule‑based scoring model to convert raw environmental data into three risk categories: Heat Risk, Flood Risk, and Air Quality Risk. Each category is scored from 0 to 100.
3. Real‑Time Visualization: The computed risk scores are rendered instantly on the 3D Climate Map. Cities and regions are color‑coded to help users quickly identify high‑risk zones.

This v1 system provides fast, reliable, and globally available risk insights using live environmental data.

• OpenWeather (Weather API):Provides temperature, humidity, rainfall, storm indicators, and city geolocation.
• OpenWeather Air Pollution API:Supplies PM2.5, PM10, NO₂, O₃, and AQI values for air‑quality risk scoring.
• Electricity Maps (Optional):Used for carbon intensity and energy‑related environmental metrics.
• GreenNeural Risk Engine:Converts raw environmental data into Heat, Flood, and Air Quality risk scores (0–100).

These sources allow GreenNeural to deliver fast, reliable, and globally available climate risk insights.