📐 Pitch Angle and Field of View (FOV) 

• Road Cross-section 

  • Tilt (Pitch): 15°–25°

  • Horizontal FOV: 60°–80°

  • Alignment: Parallel to the road axis – optimal for License Plate Recognition (LPR) and capturing vehicle side profiles.

• Intersections 

  • Tilt (Pitch): 30°–45° (can be increased to 45°–60° for large interchanges)

  • Horizontal FOV: 90°–120°

  • Note: The closer to vertical (Pitch → 90°, i.e., "bird's-eye view"), the better the visibility of traffic relations and the fewer occlusions.

• Roundabouts 

  • Tilt (Pitch): 60°–90° (optimal: vertical, Pitch ≈ 90°)

  • Horizontal FOV: 100°–130°

  • Alignment: Central mounting above the roundabout (if possible) or multiple cameras at entries – each with its own specific angle.

🌙 Night Measurement and Weather Conditions 

• Use cameras with IR (Infrared), especially in unlit areas.

• Rain, fog, or dirt on the lens → although the AI is trained on such footage, severe weather conditions can still reduce analysis effectiveness.
  
  

⚠️ Common Mounting Errors 

• Mounting too low → occlusions caused by vehicles in the foreground.

• Incomplete coverage of the intersection/roundabout → failure to count entries that are outside the frame.

• Trees in the middle of a roundabout → interrupted tracking trajectories.

• "Face-on" camera alignment instead of an angled view → causes additional occlusions.

• Frame too narrow or insufficient resolution → causes AI errors or failure to recognize objects.

🧩 Example problems and solutions

• Problem: "The camera cannot see the second lane; it is obstructed by a truck." 

  • ✅ Solution: Increase the mounting height or add a second camera. 

• Problem: "ALPR fails to recognize plates at dusk." 

  • ✅ Solution: Reduce the camera's shutter speed or increase the FPS (frames per second). Both solutions improve image sharpness. 

• Problem: "ALPR fails to recognize plates at night." 

  • ✅ Solution: The camera must be equipped with IR illumination, and the light's angle of incidence should be 45 degrees.