Replication Data for: Development of Cost-Effective Sensing Systems and Analytics (CeSSA) to Monitor Roadway Conditions and Mobility Safety

  • Chun-Hsing Ho (Northern Arizona University) (Creator)
  • Chun-Hsing Ho (Contributor)

Dataset

Description

Products of Research: All field data collected for this research was vibration responses from five sensors mounted on a vehicle that travelled on the I-10 corridors in Phoenix. All vibration data was used to analyze and predict pavement conditions using Matlab, R, Excel, and ArcGIS. Data Format and Content: The format of all vibration data is in a csv file that was further converted to a .xls format. For computing purposes, all vibration data were analyzed against their accuracy for prediction of pavement conditions using Matlab (in a m. format) and python (in a .ipynb format). For statistical analysis purposes, all vibration were analyzed using R software and the output files are in .rmd format. When pavement conditions were identified, maps were created using ArcGIS software and its format is in a .mxd format.
Date made availableMay 12 2021
PublisherHarvard Dataverse

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