A team of researchers at Australia's University of Technology Sydney (UTS) has developed a machine learning method for the real-time assessment of road base compaction quality.
The intelligent compaction model processes data from a sensor attached to a construction roller.
UTS' Behzad Fatahi said the solution "incorporates machine learning and big data from construction sites to predict the stiffness of compacted soil with a high degree of accuracy in a fraction of second, so roller operators can make adjustments."
Fatahi explained compaction must be "just right" to ensure proper structural integrity and strength.
The researchers suggested this technology could support construction of longer-lasting roads that are more tolerant of severe weather.
From University of Technology Sydney (Australia)
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