Technology Stack
Model Performance
Technical Implementation
Data Collection
- Real-time weather data via OpenWeatherMap API
- Historical data from Open-Meteo
- Global coverage: 10 diverse climate locations
- Features: temperature, humidity, pressure, rain, wind
Signal Simulation
- Physics-based attenuation models
- Rain rate impact on signal strength
- Atmospheric conditions modeling
- Time-series feature engineering
ML Pipeline
- Multiple regression approaches
- XGBoost & Random Forest models
- SHAP for model interpretability
- Hyperparameter optimization
Model Evaluation
- Cross-validation across locations
- Residual analysis and diagnostics
- Feature importance analysis
- Automated reporting pipeline
Key Weather Features
Rain Rate
Primary factor affecting signal attenuation through precipitation scattering
Temperature
Influences atmospheric refraction and signal propagation paths
Humidity
Water vapor absorption impacts signal strength, especially at higher frequencies
Pressure
Atmospheric pressure variations affect signal refractive index
Wind Speed
Correlates with atmospheric turbulence and signal stability
Cloud Cover
Indicator of precipitation potential and atmospheric conditions
Global Data Coverage
Weather data collected from diverse global locations to ensure model generalization across different climates and atmospheric conditions.
North America
- Seattle, WA
- Chicago, IL
- Phoenix, AZ
- Miami, FL
- Denver, CO
- San Francisco, CA
- New York, NY
International
- London, UK
- Tokyo, Japan
- Sydney, Australia
Technical Challenges & Solutions
Integrating real-time weather data from multiple APIs
Physics-based signal attenuation modeling
Feature engineering from temporal weather patterns
Model interpretability with SHAP analysis
Global data collection across diverse climates
Business Applications
Service Quality Maintenance
Proactive monitoring helps maintain consistent satellite internet service during adverse weather conditions.
Customer Notifications
Early warning system for potential service disruptions allows customers to plan accordingly.
Resource Optimization
Dynamic power allocation and resource management based on predicted signal conditions.
Reduced Downtime
Predictive maintenance and proactive adjustments minimize service interruptions.