Page 12: 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.

Computer Sciences

Fast traffic algorithm could improve real-time traffic forecasts

Everyone hates traffic. Big cities in particular are plagued by an overabundance of vehicles, turning a simple crosstown jaunt into an odyssey during rush hour. Part of the problem is that traffic is incredibly complex, and ...

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. ...

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