Minnesota Department of Transportation Research Services Section
A data filtering system for the MnROAD temperature database was designed and implemented. Fourteen
inter-dependent quantitative tests were developed to identify and flag erroneous, questionable, or exceptional data.
Four of the tests identify missing and intermittent data streams. Three of the tests analyze the time series from individual sensors and identify outliers. Three of the tests compare data streams of similar sensors; “similar”
implies identical pavement type, general location, and sensor depth. The remaining four tests are summary tests
that identify periods of unreliable data. The specific analysis and quantitative results are based upon the 471,178,324 data records from 1,313
thermocouple sensors in 48 MnROAD test cells collected from 1 January 1996 through October 2007. The
considered test cells include both hot mix asphalt and Portland cement concrete sections from both the Mainline
and Low Volume Road.
The majority of the sensors performed very well: 714 of the 1,282 operational sensors produced reliable
data more than 99 percent of the time. Only 18 of 1,282 operational sensors produce reliable data less than 50
percent of the time. Only 31 of the original 1,313 sensor were wholly non-operational. A wide variety of statistical tables and graphical representation were produced in a digital format for the
Although this project focuses on a particular set of data, the concepts and tools developed in this project are
designed to be extensible to accommodate the filtering of the ongoing and future data collection efforts at
Minnesota Department of Transportation
Research Services Section
Barnes, Randal J..
MnROAD Data Mining, Evaluation and Quantification – Phase I.
Minnesota Department of Transportation Research Services Section.
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