Page 13: Research news on AI-enabled digital twins

AI-enabled digital twins combine high-fidelity virtual replicas of physical assets with machine learning and sensing technologies to monitor condition, predict failures, and support operational decision-making. Applications span bridges, railways, nuclear reactors, wind turbines, manufacturing equipment, and urban infrastructure, integrating structural health monitoring, non-destructive evaluation, and high-resolution imaging. Data-driven models enable real-time fault diagnosis, risk-informed maintenance, and optimization of performance, often incorporating robotics, remote sensing, and time-series domain adaptation for robust, continuous infrastructure management.

Engineering

AI could snuff out wildfires one power line at a time

Annually, tens of thousands of wildfires ravage the United States, posing significant threats to people, wildlife, and infrastructure. A percentage of those wildfires are caused by degraded or downed electrical equipment. ...

Hi Tech & Innovation

Smart packaging reveals product condition through color changes

Research conducted at the University of Vaasa paves the way for smart packaging that indicates product condition through color-changing printing inks. Doctoral researcher Jari Isohanni investigated how machine learning could ...

Hi Tech & Innovation

AI system helps prevent workplace injuries

The University of Cincinnati is working with Ohio's Bureau of Workers' Compensation to use digital-twin technology to make workplaces safer.

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