ATLAS | Locating defects of the road surface

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Reading time:
min
Data Processing & Custom Development
July 28, 2020

One of the goals was to filter small single cracks not affecting significantly road quality and only pay attention to bigger areas.

Road maintenance is a complex task requiring:

  • Localization of defect areas
  • Counting approximate area sizes for repair
  • Planning sufficient but not excessive material and human resources

Process:

  • Survey mission planned with UgCS
  • Drone: DJI Phantom 4
  • Map storage and processing: ATLAS
  • Manual annotation: approx. 15 minutes
  • Initial machine learning detector's training in ATLAS cloud: approx. 50 minutes

Result:

  • Shareable web-map with marked defects in ATLAS
  • Report with georeferenced areas in GeoJSON


Here is an example of how areas with cracked asphalt can be identified with Atlas: CASE#1


Client: G2 INGENIERIA PARA LA CONSTRUCCIÓN S.A. DE C.V.#nbsp;

Country: Mexico

Industry: Civil Engineering, Construction & Maintenance


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