Tarmac Safety AI

An automated system for detecting foreign object debris (FOD) on airport runways is developed using Roboflow, which integrates the RF-DETR model for localizing debris and pavement holes, and Gemini 2.5 Pro for classifying objects and generating inspection summaries. This system addresses the high economic impact of FOD, estimated at $22.7 billion annually, by offering a continuous and efficient solution compared to traditional manual inspections. The process involves training the RF-DETR model on a public FOD dataset, achieving high accuracy with 99.0% mAP@50, and deploying the model within a Roboflow Workflow. This pipeline allows for the detection and annotation of debris on runways, providing maintenance personnel with precise locations of potential hazards. The workflow is adaptable to airport-specific datasets to account for unique conditions, and can be enhanced with surveillance technologies to improve detection and reporting, ultimately aiding in runway safety and maintenance efficiency.

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