InFlightAI Computer Vision Model
Hotspot Detection
AI Model Overview
InFlightAI’s Hotspot Detection model uses real-time thermal analysis to identify localized high-temperature areas on equipment, wiring, infrastructure and ground surfaces. Designed for live monitoring workflows, it highlights critical risk zones that may indicate imminent failure or the risk of wildfire, enabling rapid response and improved operational safety.
The thermal feed is read in flight, with each region compared against its surroundings rather than against a fixed threshold. A thermal-capable payload is required.
A thermal risk surfaces while the crew is still on site and able to act. Warm components are separated from failing ones, keeping response focused on real risk, and coverage extends to the ground and vegetation heat that can precede ignition.
How It Works
Hotspot Detection returns segmentation mask output. It identifies localized high-temperature areas on equipment and wiring, hotspots on infrastructure and ground surfaces, heat signatures indicating imminent failure, and ground or vegetation heat associated with wildfire risk.
Hotspot 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 in real time while the flight is still in the air, so alerts reach the team before the aircraft lands. The model is configured to the assets and environments at your site during onboarding, and is ready for use within thirty days.