InFlightAI Computer Vision Model
Crack Detection
AI Model Overview
InFlightAI’s Crack Detection model uses high-resolution computer vision AI to identify surface cracks in structures such as walls, foundations, and equipment. It detects fine and large-scale defects, supporting structural integrity assessments and maintenance planning.
High-resolution imagery lets the model separate genuine surface cracking from the shadow, seam and joint lines that look similar at a glance. It is configured against your surfaces and materials during onboarding.
Cracking is caught early enough to monitor on a schedule rather than repair under outage. Hairline and structural cracks are distinguished from one another, so crews prioritize by risk instead of by whichever asset happened to be inspected last.
How It Works
Crack Detection returns segmentation mask output. It identifies surface cracks in walls, foundations and equipment, covering everything from fine hairline cracking through to larger structural defects.
Crack Detection is an asset maintenance model, currently deployed across industries like Electric Utilities, Oil & Gas, Manufacturing, Logistics, Power Generation, Nuclear and Mining. 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.