Development of Measurement Model Using Filter Technique
Anomaly Detection and Automatic Data Correction
Enhancing Reliability by Supplementing Existing Methods
[Sejong=Asia Economy Reporter Moon Chaeseok] Korea Rural Community Corporation announced on the 16th that it has developed a measurement model that improves the accuracy of reservoir water level measurement using a filtering technique. It is now possible to automatically correct reservoir water level data and detect abnormal values.
The corporation explained that this is a new quality control model that can quickly and accurately measure reservoir water levels in preparation for increasingly severe abnormal weather such as heavy rain. Among the reservoirs managed by the corporation, automatic water level gauges are installed in about 1,600 reservoirs with an effective storage capacity of over 100,000 tons, measuring water levels every 10 minutes via wireless communication.
Until now, immediate management was difficult because measurement data had to be corrected. This was because it was difficult to correct data errors in real time due to device defects or sensor malfunctions.
A rapid and accurate reservoir water level measurement model developed by the Korea Rural Community Corporation. (Source: Korea Rural Community Corporation)
The new model strengthens data supplementation by detecting or removing anomalies such as automatic measurement omissions or maximum/minimum outliers within the system. Additionally, it established quality classification standards so that the precision of production, analysis, and storage of each data can be immediately distinguished. As a result, the reliability of the data is increased.
Based on this research achievement, the corporation plans to apply an advanced water level measurement program starting this year and disclose related data on the Rural Water Comprehensive Information System so that the general public can easily access it.
Kim Insik, president of the corporation, said, "This research and development has made it possible to secure accurate basic data, which is the foundation of the big data era," and added, "We will strive to establish a data-driven water management response system to enhance the effectiveness of disaster response caused by climate change."
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