Qii.AI Announces Release of Road Defect Detection Module for Remote Digital Inspections

Qii.AI Announces Release of Road Defect Detection Module for Remote Digital Inspections

Qii.AI, a global leader in providing AI-enabled, computer vision and data management software solutions for asset management and digital inspections, has announced the release of its Road Defect Detection (RDD) Module, enabling automatic detection and classification of potholes, cracks, and other defects in road surfaces, within the Qii.AI platform. According to Stéphane Bouvier, the CEO of EXO Tactik, a Quebec-based provider of drone inspection services that has partnered with Qii.AI in the province, “…this technology is arriving just in time to satisfy a rapidly expanding need to manage and interpret data from drone-based road inspections.”

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Qii.AI Announces Release of Road Defect Detection Module for Remote Digital Inspections 1

Since its launch in 2020, the Qii.AI platform has distinguished itself as the most advanced suite of visual data management and analysis applications available for producers and consumers of visual inspection data. The Qii.AI platform uniquely enables users to rapidly label, train, and manage data to achieve AI functionality at scale.

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Commenting on the release of the RDD Module, Qii.AI CTO, Dr. Gunho Sohn said, “Engineers face formidable challenges effectively inspecting, tracking, and managing road surface conditions. Qii.AI’s RDD Module allows users to train their own AI-enabled visual inspection functions, end-to-end. Qii.AI’s RDD innovations create the option to automatically detect, categorize, and grade problems in the road surface  – that is to create intelligence to help manage road maintenance and repair planning, in the most-efficient, user-defined manner. With RDD’s multi-modal AI functions, users can easily generate consistent and accurate training data and define and control quality tolerances. This unique feature allows our users to continuously improve their unique AI’s performance, throughout the lifecycle of their RDD project.”

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