Prexus Atmos — Planetary Intelligence Platform

Real-time AQI, weather, fire detection, and atmospheric analytics.

GitHub Pages runs the frontend in static demo mode; provide ?api=<backend>/api/v1 for live data.

Architecture

Frontend (HTML/CesiumJS)
↓
Go API Gateway :8080
↓
Python Data Engine :8000
├── Open-Meteo (weather + AQ) — FREE, no key
├── WAQI / AQICN — FREE key required
└── NASA FIRMS — FREE key required

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Real Data Sources

Source	Data	Key needed
Open-Meteo	Weather, PM2.5, PM10, NO2, O3, SO2, CO, AQI	❌ None
WAQI / AQICN	Station AQI, dominant pollutant	✅ Free
NASA FIRMS	Active fire detections (VIIRS)	✅ Free
Nominatim	Geocoding / reverse geocoding	❌ None

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Quickstart

1. Get free API keys

• WAQI: https://aqicn.org/data-platform/token/
• NASA FIRMS: https://firms.modaps.eosdis.nasa.gov/api/

2. Configure environment

cp .env.example .env
# Edit .env and set WAQI_TOKEN and NASA_FIRMS_KEY

3. Run with Docker Compose

docker compose up --build

Frontend: http://localhost:3000
Gateway: http://localhost:8080/health
Engine: http://localhost:8000/docs

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Run without Docker

Python Data Engine

cd data_engine
pip install -r requirements.txt
uvicorn main:app --reload --port 8000

Go API Gateway

cd backend
go mod tidy
go run .

Frontend

Open frontend/index.html in a browser or serve it:

cd frontend
python -m http.server 3000

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API Reference

GET /api/v1/weather/current?lat=&lon=
GET /api/v1/weather/forecast?lat=&lon=&days=7
GET /api/v1/weather/hourly?lat=&lon=&hours=48
GET /api/v1/aqi/current?lat=&lon=
GET /api/v1/aqi/forecast?lat=&lon=&hours=72
GET /api/v1/aqi/stations?lat=&lon=&radius=25000
GET /api/v1/aqi/heatmap?lat=&lon=&resolution=0.25&radius_deg=2
GET /api/v1/satellite/fires?lat=&lon=&radius=500
GET /api/v1/satellite/smoke?lat=&lon=
GET /api/v1/alerts/active?lat=&lon=
GET /api/v1/alerts/history?lat=&lon=&days=7
GET /api/v1/analytics/aqi-trend?lat=&lon=&hours=168
GET /api/v1/analytics/health-risk?lat=&lon=
GET /api/v1/analytics/pollution-sources?lat=&lon=
GET /api/v1/dashboard?lat=&lon=

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Stack

Layer	Tech
Frontend	Vanilla JS, CesiumJS 1.122, Canvas sparklines
Gateway	Go 1.22, Gin
Data Engine	Python 3.12, FastAPI, httpx
Cache	In-memory (default) or Redis
Infra	Docker Compose, Nginx

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Feature Expansion

The architecture is designed for Prexus Atmos modules:

• Atmos Vision — satellite imagery overlays (Sentinel-5P via Copernicus)
• Atmos Radar — precipitation radar from NOAA/MRMS
• Atmos Predict — LSTM/TFT AQI forecasting model (replace Open-Meteo fallback)
• Atmos Earth — Digital twin storm/flood simulation
• Atmos Sentinel — IoT sensor ingestion via MQTT