Researchers at the University of Surrey in the U.K. have developed an algorithm that compresses big data from bridge monitoring systems into more manageable sizes.
The researchers used a dictionary learning method called K-means Singular Value Decomposition to compress data from the Bridge Weight-in-Motion system, which monitors the Leziria Bridge in Portugal.
The team applied the new algorithm to 45,000 data per channel per hour received by the bridge’s monitoring system, and reconstructed the information with less than 0.1 percent of the data lost.
"We believe that this approach shows that you can dramatically reduce the large data into a much manageable size without losing information—which is critical to structural engineers," says University of Surrey researcher Ying Wang.
From University of Surrey
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