Technical Description
The technology introduces a system for predicting weather events that utilizes deep learning to enhance predictions on local and hyperlocal scales. Integrating diverse data with advanced algorithms and LSTM-based neural networks improve accuracy by 15% to 100% over traditional models, aiding disaster management, agriculture, energy, and urban planning through reliable forecasts and early warnings.
Problems Addressed
- Models Inaccuracies
- Complex Atmospheric Condition
- Computational Errors
- Limited Updating Frequency
Tech Features
- Enhanced Prediction Accuracy
- LSTM-based Models
- Scaling Factors Incorporation
- Hardware Integration
- City-Scale Disaster Mapping
- Real-Time Alert Systems
Target Audience
- Aviation Industry
- Agriculture Sector
- Transportation & Logistics
- Disaster Management Authorities
Tech ID: P02-1979 TRL 7 Patent Status: Granted Available For Exclusive and Non-exclusive License
