InFlightAI Computer Vision Model
Unexpected Water Detection
AI Model Overview
InFlightAI’s Unexpected Water Detection model uses computer vision AI to identify unexpected water presence and accumulation across operational environments. It detects flooded areas, pooling water, and abnormal moisture conditions that may indicate drainage issues and safety hazards.
Water is identified by reflectivity and surface behavior against the ground beneath. Configuration during onboarding excludes expected water — retention ponds, washdown areas — from detection.
Pooling and flooding are flagged as signals of a drainage failure or a leak upstream. Water around equipment and foundations is caught where it does the most damage over time.
How It Works
Unexpected Water Detection returns segmentation mask output. It identifies pooling and standing water, flooded areas, and abnormal moisture conditions around equipment and foundations.
Unexpected Water 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.