Road Surface Analysis using AI tools

Road surface analysis using artificial intelligence (AI) tools involves the use of machine learning and computer vision techniques to assess and monitor the condition of road surfaces. This technology can be crucial for transportation agencies and city planners to identify road maintenance needs, ensure road safety, and optimize road infrastructure investments.

AI Artificial Intelligence tools scan the images collected from the road inspection. They identify:

  • Surface type
  • Number of potholes,
  • Weight cracks surface,
  • Thermal cracks length in a road section and
  • Raveling area.

By implementing AI tools for road surface analysis, transportation agencies can streamline maintenance efforts, reduce costs, improve road safety, and extend the lifespan of road infrastructure. Continuous monitoring and data-driven decision-making are key components of effective road management strategies.

Results from AI Analysis are stored in cloud database (Road Plan Pavement Management System) and are available for further research and reporting.

road surface type

Surface Type Recognizer identified road type as asphalt.

road surface distresses

AI Artificial Intelligence tool for identifying weight cracks determined condition of the road as 49, on the scale 0-100.

Whole set of images from the road section evaluates condition as 88.

Google map is showing position of the image.