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The deterioration and collapse of aging infrastructure is a pressing concern worldwide. Now, researchers at Michigan State University (MSU) have developed an innovative “deploy-and-forget” system that assesses the health of critical structures using sensors and artificial intelligence (AI), before and after potentially damaging events.
According to TechXplore, this system, named MIDAS (Mechanics-Informed Damage Assessment of Structures), is designed to autonomously monitor infrastructure using low-cost sensors. By learning the behaviors and patterns of a healthy structure, MIDAS can detect and locate damage early, well before it poses a significant risk. It utilizes mechanical knowledge to improve its accuracy, enabling it to spot issues that traditional systems might overlook. The research is published in Nature Communications.
The key advantage of MIDAS is its ability to assess damage in real-time. Once installed on a structure, it creates a custom baseline model based on the bridge or building’s initial state. After a certain damaging event, MIDAS rechecks the structure, immediately alerting engineers if any issue is detected. This early warning system allows for timely repairs, potentially preventing catastrophic failures.
The team likened the technology to a “precision health” monitoring system for infrastructure. Just as a smartwatch detects heart abnormalities before symptoms appear, MIDAS can “listen” for structural issues and send alerts before they escalate. This could have been an important preventative measure in recent structure collapses. Tor example, the researchers explain that following natural disasters similar to the recent wildfires in Los Angeles, MIDAS could assess the damage to bridges and roads in real time, providing crucial data for emergency response teams and ensuring safer evacuations.
With infrastructure aging and repair budgets limited, MIDAS offers a cost-effective solution to maintain and monitor essential public structures, enhancing safety and resilience across communities.
