Rain Sensor Data Validation Using Radar Similarity Coefficients
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Solution Overview
Problem
Current methods for controlling fluidic networks, such as sewerage systems, face challenges in dynamically adapting operations in real-time due to unreliable rainfall data from meteorological radars and rain gauges, which lack precision and consistency, leading to potential economic and human consequences.
Innovation Solution
A computer-implemented method that validates rainfall data by calculating similarity coefficients between data from rain gauges and meteorological radars, identifying valid data through geographical and temporal analysis, and aggregating results to ensure reliable input for real-time control decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If rainfall data from meteorological radars and rain gauges is used for real-time control of fluidic networks, then dynamic control capability is improved, but data reliability deteriorates due to mechanical defects, poor positioning, and orientation issues of rain gauges
Solution Approach 1:
The patent introduces an intermediary validation system that acts as a mediator between raw rainfall data from multiple sources (radars and gauges) and the control system. This validation device cross-references data from multiple probes and radars, using similarity coefficients to identify valid data and filter out defective readings, thereby ensuring reliable input for real-time control without sacrificing dynamic responsiveness
Solution Approach 2:
The validation process implements feedback by continuously comparing rainfall data from multiple sources and using similarity coefficients to identify consistent patterns. Data that deviates from the pattern (indicating potential defects) is flagged for validation or rejection, creating a self-correcting system that improves data reliability while maintaining real-time control capability
2Measurement precision
If data validation is performed using only probe data or only radar data, then processing simplicity is maintained, but measurement precision deteriorates due to inherent limitations of each individual data source
Solution Approach 1:
The patent merges data from multiple probes and radars into a unified validation process. By combining multiple data sources and calculating similarity coefficients across them, the system achieves higher measurement precision for precipitation intensity while managing complexity through systematic comparison and validation algorithms
Solution Approach 2:
The validation process applies partial action by focusing validation efforts on specific conditions - when similarity coefficients indicate potential issues. Rather than validating every data point equally, the system intensifies validation where needed (when data consistency is questionable) and accepts data where confidence is high, optimizing the balance between precision and complexity
3Loss of time
If traditional data validation methods are used without real-time processing, then computational complexity is reduced, but loss of time increases due to delayed validation results
Solution Approach 1:
The system performs preliminary action by pre-establishing validation rules, similarity coefficient thresholds, and data comparison protocols before real-time operation. This preparation allows the validation process to execute efficiently during real-time control without excessive computational overhead, reducing validation delay while managing complexity through pre-configured parameters
Solution Approach 2:
The validation process uses periodic action by evaluating data at regular intervals and using temporal patterns in similarity coefficients to identify valid data. This periodic approach structures the complex real-time validation into manageable cycles, reducing computational burden while maintaining timely validation results for dynamic control
Data Source
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AI summary
The invention relates to a method for the real-time validation of data provided by a rain sensor. The method comprises steps of: - receiving, over a given time window, rain data from a sensor and weather data from at least one weather radar; - calculating a coefficient of sensor/radar similarity between the rain data received from said sensor and the weather data received from said at least one weather radar; - comparing the obtained value of the coefficient of sensor/radar similarity with a sensor/radar threshold value; and - validating the rain data from said sensor if the value of the coefficient of sensor/radar similarity is greater than or equal to the sensor/radar threshold value.