ARUP

Arup, a leading global engineering firm headquartered in London, England, regularly conducts tunnel inspections as part of its global infrastructure practice. The Arup team was looking for tools to improve the inspection process and ultimately, boost the ability to quantify infrastructure data for defects like cracks in tunnel walls.

In the case study, you'll see how:

  • Smartvid.io's machine-learning engine helped detect defects in tunnel walls 
  • Arup was able to leverage the power of computer vision to create quantitative measures of tunnel health
  • the Arup team is now offering computer vision-based analysis to clients as part of its infrastructure inspection program

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After the pilot project, we were convinced these new techniques create additional value for our clients by enabling a quantitative assessment of key infrastructure health indicators like cracks. In the future, we look forward to expanding these models to other indicators of damage, including concrete spalling and water ingress features.— Mike Devriendt, Associate Director
 
ARUP