Machine vision and AI in railroad services

Machine learning is an important asset to predict where track maintenance will be needed.

Daily updated spatial database on objects in the railway environment – a great tool in supervision and asset management.
After detected objects are entered in the database, it is possible to check the same object, to determine its status, its existence or absence with each new survey.

Railway detection with machine vision

  • Determination of track planes and gradients
  • Detection of faults in tracks and superstructures, platform sloping
  • Comparison with a database of 3D point clouds and indication of deviations
  • Analysis of point cloud deviations generated in a given time range
  • Comparison with 2D GIS databases
  • Integration of existing GIS data and integration into the enterprise system
  • Building a continuous and automatic learning system, using affordable sensors, we can update an expensive spatial database based on point clouds and detect deviations against the baseline state
  • Thanks to dense sampling, our detections are accurate and detailed

MOUNTED CORONA CAMERA CORE

D.I.Y ADD OEM CORONA DETECTION CAPABILITIES TO YOUR SYSTEM

  • HD camera
  • Compact dimensions
  • Built-in video recorder
  • Highest sensitivity to UVv
  • Adjustable FOV
  • Bi-Spectral UV-Visible
  • Fit for speedy inspections
  • Corona events counting
  • Camera core for OEM
  • Communication protocols

VISION BASED RAILWAY TRACK MONITORING USING DEEP LEARNING

AUTOMATED TRACK INSPECTION USING COMPUTER VISION AND PATTERN RECOGNITION METHODS

  • Observation of structural defects
  • Building an automatic learning system
  • Detection of predefined types of errors in images captured by cameras mounted on infrastructure manager equipment
  • Research and support of diagnostic-based maintenance options
  • We focus on deviations only and detect potential errors between deviations

This is how our system works. The video shows object detection in real-time by our train mounted sensor system.

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