Drexel researchers create AI system to spot cracks in infrastructure

An article from
site logo

Dive Brief

The team wants to use the same technology leveraged in facial recognition and drug development to flag warning signs in aging public works.

Published Feb. 7, 2024

A robot sits on a bed of concrete. It's sleek and off-white, with a visual lens on the front.

A research team at Drexel University created a system that uses a robot scanner, computer vision and machine learning programs to identify, model and monitor cracks in concrete.

Courtesy of Drexel University

This audio is auto-generated. Please let us know if you have feedback.

Dive Brief:

  • A team of researchers from Drexel University in Philadelphia created an AI-based system to inspect roads and bridges that can flag and monitor cracks before they develop into bigger issues.
  • The research team wants to augment visual inspection technologies with a new machine learning approach that combines computer vision, which allows machines to recognize and understand objects, with a deep-learning algorithm to pinpoint problem areas, according to a Drexel press release. Combined with autonomous robots, researchers said the approach could help efficiently inspect and identify problem areas in infrastructure.
  • Once an issue is spotted, the process then conducts a series of laser scans of the region to create a digital twin of the structure that humans can use to assess and monitor the damage, including tracking crack growth over time, according to the release.

Dive Insight:

Drexel’s method, which researchers published in the journal Automation in Construction, uses a high-resolution stereo-depth camera to record images of a structure before feeding them into a deep-learning program called a convolutional neural network. 

These systems can spot the finest of patterns and discrepancies in massive volumes of data, researchers said, with applications previously used in drug development, deepfake detection and facial recognition technology.

Arvin Ebrahimkhanlou, an assistant professor at Drexel’s College of Engineering and a member of the research team, told Construction Dive that the team has been in contact with the National Academy of Building Inspection Engineers throughout the design process. 

“The neural network has been trained on a dataset of sample cracks, and it can identify crack-like patterns in the images that the robotic system collects from the surface of a concrete structure,” Ebrahimkhanlou said in the release. “We call regions containing such patterns, regions of interest.” 

While the technology has been tested in a lab setting, Ebrahimkhanlou told Construction Dive the team needs a partner to test it in the field, which will take at least a few years.

In its latest assessment of America’s infrastructure, the American Society of Civil Engineers found a $786 billion backlog on road and bridge repairs alone.

Note: This article have been indexed to our site. We do not claim legitimacy, ownership or copyright of any of the content above. To see the article at original source Click Here

Related Posts
The Great Reset And The Rise Of Bitcoin thumbnail

The Great Reset And The Rise Of Bitcoin

While our economy is known for working in cycles of growth and decline, we know that this is a phenomenon that started only in the last century. Before that point, our economy didn’t work with a system that relied entirely on debt. It is this new reliance on debt leading to growth that started these…
Read More
After Celo’s success, Polkastarter integrates Avalanche thumbnail

After Celo’s success, Polkastarter integrates Avalanche

Avalanche › DeFiPolkastarter’s integration of Avalanche will further its goal to become multi-chain.As part of its efforts to achieve its multi-chain goal, Polkastarter has officially announced the integration of Avalanche.Polkastarter integrates Avalanche into its platformThe move to integrate Avalanche commenced following the success recorded by the last integration exercise by the company. The exercise led…
Read More
Laschet's election debacle: “Digital Brain Drain” - election results cost Union important digital skills thumbnail

Laschet's election debacle: “Digital Brain Drain” – election results cost Union important digital skills

Die CDU/CSU-Fraktion ist von bisher 245 auf jetzt 196 Sitze geschrumpft. Im neuen Bundestag sind damit viele Fachpolitiker nicht mehr dabei. Besonders deutlich traf es die Digitalexperten der Union.Die Arbeitsgruppe „Digitale Agenda“ der Fraktion ist mit einem Mal führungslos geworden. Der Vorsitzende Tankred Schipanski (Thüringen) verpasste ebenso den Wiedereinzug ins Parlament wie sein Vize Maik…
Read More
Index Of News
Total
0
Share