Weather Prediction Server Using Segmented Observation Points

The patent segments the weather prediction system into multiple observation points distributed across different locations. Each observation point collects local weather data independently, allowing the system to maintain broad coverage while providing precise, location-specific predictions. This segmentation enables the system to overcome the limitation of coarse-grained administrative district forecasts.

The patent implements local quality by creating observation points at specific locations that collect and analyze weather data for their immediate surroundings. Each observation point provides weather predictions tailored to its local environment, allowing users to obtain accurate weather information for specific points along their travel paths rather than relying on averaged regional forecasts.

The patent divides the prediction system into multiple independent observation points, each responsible for collecting and analyzing weather data in its local area. This segmentation allows the system to maintain high productivity by providing predictions for many locations simultaneously while ensuring accuracy for each specific section through localized data collection and analysis.

The patent introduces observation points as intermediary elements between the weather prediction system and the user. These observation points act as mediators that collect raw weather data, process it through machine learning models, and provide accurate predictions for specific locations. This intermediary approach enables the system to scale coverage while maintaining precision through localized data processing.