AI-powered disaster prediction system for Libya using machine learning models to predict floods, storms, and other natural disasters
# Libya Disaster Prediction AI System
A production-grade AI-powered disaster prediction system for Libya, featuring hybrid ensemble learning, time-series intelligence, and real-time risk assessment.
## π Features
- **Hybrid Risk Engine**: Combines XGBoost ML, Isolation Forest anomaly detection, trend analysis, and geographic risk
- **Time-Series Intelligence**: Rolling averages, deltas, and spike detection for early warning
- **Probability Calibration**: Isotonic calibration for realistic confidence estimates
- **Confidence-Based Alerts**: HIGH_CONFIRMED vs HIGH_UNCERTAIN classification
- **Risk Stability Tracking**: Monitors risk trends (rising/falling/stable) across predictions
- **Early Warning Detection**: Pre-disaster pattern recognition
- **Real-Time Feedback Loop**: API for collecting real-world event verification
- **Geographic Awareness**: Coastal proximity and elevation-based risk factors
## π Architecture
```
Data Layer
βββ Weather API (air pressure, quality, risk scores)
βββ Marine API (wave height, wind speed, sea level)
βββ News API (article counts, keyword analysis)
βββ Geolocation (lat, lon, elevation, distance to coast)
```
## π Data Sources
The system integrates data from multiple sources to provide comprehensive disaster risk assessment:
### 1. Copernicus Marine Service
- **Provider**: Copernicus Marine Environment Monitoring Service (CMEMS)
- **Data**: Sea level anomalies, wave height, wave period, wind speed, swell wave height
- **Coverage**: Mediterranean Sea, Libyan coastal waters
- **Access**: Requires API key from Copernicus Marine
- **Usage**: Marine conditions that contribute to flood and storm surge risks
### 2. Weather API
- **Provider**: OpenWeatherMap or similar weather service
- **Data**: Air pressure, air quality index, weather risk scores, temperature
- **Coverage**: Libyan cities (Tripoli, Benghazi, Derna, etc.)
- **Access**: Requires API key from weather service provider
- **Usage**: Atmospheric conditions that indicate s β¦