Weather Station Subset Selection for Accurate Local Estimation
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Solution Overview
Problem
Existing weather station systems face challenges in providing accurate weather estimates at specific locations due to the abundance of weather data from numerous stations, leading to inefficiencies and potential inaccuracies in weather reporting and navigation.
Innovation Solution
A method is developed to select a subset of weather stations based on their average distance and location relative to a specific location, using weighted averages and predefined criteria, to optimize weather data collection and reduce computational complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If weather data is collected from all available weather stations, then the quantity of weather information increases, but the accuracy of weather estimation at a specific location deteriorates due to inclusion of irrelevant distant station data
Solution Approach 1:
The patent segments the set of all weather stations into a selected subset based on their spatial relationship to the target location. By dividing the complete dataset into relevant and irrelevant portions, the system processes only the segmented subset that contributes to accurate local weather estimation, thereby maintaining data quantity benefits while eliminating precision-deteriorating elements.
Solution Approach 2:
The patent applies local quality by selecting weather stations based on their proximity and spatial distribution relative to the specific location of interest. Different locations will have different optimal subsets of weather stations, allowing the system to tailor the data source composition to local conditions, thus improving estimation accuracy without sacrificing the overall quantity of available weather information.
2Reliability
If a large number of weather stations are used for weather estimation, then the completeness of weather data improves, but the computational complexity increases due to processing numerous station combinations
Solution Approach 1:
The patent extracts only the necessary subset of weather stations required for accurate local weather estimation, removing redundant distant stations from the processing pipeline. This extraction maintains the reliability and completeness of weather data for the specific location while significantly reducing the computational complexity associated with evaluating all possible station combinations.
Solution Approach 2:
The patent employs partial action by selecting a specific number and configuration of weather stations that is sufficient for accurate estimation rather than using all available stations. The system determines the optimal subset size and composition, performing just enough data collection and processing to achieve reliable results without the excessive computational burden of complete dataset analysis.
3Area of stationary object
If all weather stations within a predefined area are processed, then the coverage of weather data improves, but the processing time increases due to evaluating multiple station combinations
Solution Approach 1:
The patent performs preliminary action by pre-selecting and organizing weather stations based on their spatial relationships to potential target locations before actual weather estimation is required. This preliminary organization of weather station subsets based on geographic criteria enables rapid retrieval and processing during actual weather reporting, maintaining comprehensive area coverage while minimizing real-time processing time.
Data Source
AI summary
A method is provided herein for selecting a combination of a subset of weather stations from among a plurality of weather stations for estimating the weather at a specific location. The method may include: receiving an indication of a plurality of weather stations within a predefined area, where the predefined area includes a first location; determining, for each of the plurality of weather stations, a distance of the weather station from the first location; calculating, for a plurality of different combinations of subsets of the plurality of weather stations, an average distance of the weather stations of each of the plurality of different combinations from the first location; calculating, for each of the different combinations of subsets, an average location relative to the first location; and selecting a combination of a subset of the plurality of weather stations based on the average distance and the average location.