Ural scientists have created AI to search for cracks in infrastructure

Ural Federal University has created a neural network system with artificial intelligence (AI) capable of automatically detecting defects in bridges, roads and other infrastructure facilities. This was reported by Izvestia on August 5.

As specified, the algorithm analyzes video data received from drones and is able to detect cracks in a matter of seconds. The efficiency of the technology when tested on real personnel from Russia and China was 88.7%.

Today, the condition of infrastructure facilities is monitored manually. At least three specialists will be involved in the inspection of one large structure.

"The inspection of a large structure requires a lot of time. And not all areas can be reached by a person, so you have to use additional body kits and even attract climbers. In some cases, they try to use drone footage. However, you still have to watch large amounts of video later. Our technology will replace hours—long manual inspections, reduce the risk of accidents and save the budget on infrastructure maintenance," said Zoya Belyaeva, Head of the UrFU Department of Building Structures and Soil Mechanics.

A special feature of the system is the ability to simulate the way a person's gaze focuses. In addition to the usual video images, infrared imaging is also used, which expands the possibilities for detecting damage that are not available with standard visual inspection.

The university also noted that technology can significantly simplify the work of many specialists.

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Earlier, on July 31, a medical AI assistant developed by Russian specialists at the AI Institute based on the GigaChat neural network model achieved 93% accuracy in detecting diseases during the test. Earlier, a similar system from Microsoft achieved an 85% rate in a similar experiment, the creators of the domestic product told Izvestia.