Photo: UCF
Necati Catbas and his team are developing tools that use sensors, AI and machine learning to help spot structural defects before they're visible to the human eye.
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Artificial Intelligence
Road Doctor
A University of Central Florida engineering professor is pioneering systems to monitor the structural integrity of aging roads, bridges and buildings.
As an engineering student, University of Central Florida Professor Necati Catbas studied structural damage caused by earthquakes. He wanted to learn how buildings could be made more resilient and safer.
But his focus changed while studying for his doctorate at the University of Cincinnati. America built the first national transportation network, he thought, but those roads and bridges were nearing the end of their 50-to-75-year life spans. What happens next? How could engineers better monitor their structural integrity?
“I realized this was a major national and also international need,” he says.
Artificial intelligence and programmed learning will play a big part in assessing the risks, and Catbas, director of UCF’s Civil Infrastructure Technologies for Resilience and Safety Initiative, is working to pioneer the systems needed. He calls it structural health monitoring, which employs sensors and cameras to gather data to complement the traditional, hands-on inspections and create “a more comprehensive evaluation of the building’s health.”
The sensors can measure vibrations, gauge stress and more, while cameras can feed image-based applications with numerous pictures taken over extended time. The monitoring system can analyze mass amounts of data to identify structural changes and anomalies earlier, before they may be noticeable to the human eye.
“One of the challenges with these technologies was analyzing and poring over all the data generated by the sensors,” Catbas says. “It can identify changes in structures and patterns to predict what’s happening.”
Inspections on most structures occur annually at best. With the sensors and cameras used in structural health monitoring, data continues to be gathered and fed into the AI system. In addition, AI can anticipate problems in road networks such as Interstate 4 without each and every section being physically examined.
“The bridges and overpasses are going to be pretty consistent,” Catbas says.
He compares the system to human health monitoring: Structures also age. Surgery to remove damaged or diseased organs is akin to repairing and retrofitting a building, a bridge, dam or pipelines. For younger structures, it’s useful to establish baseline data to track performance and health over time. It helps identify anything out of the ordinary to know when additional investigation is needed.
It could be five to 10 more years before his system is available on the market. He is seeking patents and says guidelines must be developed for its use. But it is being tested in the field, and state transportation officials sometimes ask for it to be used in specific cases.
