5 Ways AI Improves Sewer Video Inspection Accuracy

  1. Remove Sewer Televising Operator Bias
    • Often times Sewer Camera Operators retain Bias from the last project they recently Televised.  If an operator just completed a project where Roots were very prevalent, roots are on the operator’s mind and the sewer televising operator may be seeking out Roots more than other types of pipe defects.  AI algorithms have no residual bias.  Defects are marked based on trained algorithms of several thousand sewer defect types and categories.
  2. AI-powered sewer diagnostics are more thorough than manual sewer defect detection
    • Sewer Televising Operators typically do not mark every defect within a sewer pipe.  Often Operators will mark a particular defect and use a defect extension “Continual Defect”. The “Continual Defect” technique diminishes the visual accuracy of the projected overall pipe condition.  AI sewer defect detection marks far more defects than the “Continual Defect” technique. Automated sewer defect detection contributes to a more robust overall pipe condition assessment report.
  3. Increased Operator Focus on Sewer Camera Operation
    • Currently most Sewer Televising Operators use software that requires action when encountering and identifying a defect.  Typically, an operator must select a defect severity level from a computer pull down screen menu.  This technique removes focus and attention from the sewer camera within the sewer pipe.  AI sewer defect detection eliminates the need for removing focus from the operation of the $30,000 plus value of sewer camera equipment inside the pipe.  Focusing mostly on operating the sewer equipment, within the sewer pipe, contributes to increased operator skill level and possibly reduced equipment repair expenses.
  4. Lessens Operator Production Pressure
    • Many Sewer Televising Operators feel the pressure of televising a required minimum amount of footage daily.  Logging sewer defects manually takes time. Automated sewer defect detection speeds up sewer televising, by mitigating the data entry time and increasing sewer televising camera movement time.
  5. Eliminates Consulting Engineer Evaluation Bias
    • Many municipalities use consulting Civil Engineers or in house municipal staff Engineers.  When Engineers evaluate sewer televising video, they encounter similar biases that sewer televising operators encounter.  When Engineers see the designation “Continual Defect” it forces the Engineer to watch the entire sewer televising video. Manual sewer televising video evaluation is a time consuming and tedious job.  Defect identification bias is often times a byproduct of evaluating sewer televising videos.  AI sewer defect detection mitigates sewer video evaluation bias and fatigue.
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