InFlightAI Computer Vision Model
Cross Arm Condition
AI Model Overview
InFlightAI’s Cross Arm Condition model uses computer vision AI to assess cross arm alignment and structural condition. It detects tilt, warping, and material degradation such as wood splitting or rot, helping identify stability risks and prioritize maintenance.
The model locates the cross arm at pole top, then classifies alignment and material condition as separate passes. It is configured to the arm types on your network during onboarding.
Tilt and rotation are identified before a cross arm fails under load or storm. Cross Arm Condition becomes a ranked work list rather than a climb-and-look exercise, covering spans that would otherwise wait years between physical inspections.
How It Works
Cross Arm Condition returns bounding box output. It identifies tilt and misalignment, and warping.
Cross Arm Condition is an asset maintenance model, currently deployed across industries like Electric Utilities and Power Generation. Detections are returned after the flight has landed, once imagery and waypoint data have been synced to the platform. The model is configured to the assets and environments at your site during onboarding, and is ready for use within thirty days.