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.
Machine learning & AI
The advent of generative artificial intelligence has sent shock waves across industries, from the technical to the creative. AI systems that can generate viable computer code, write news stories and spin up professional-looking ...
Mar 17, 2025
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21
Engineering
A researcher from VUB has developed a system that can predict wind turbine failures caused by early component malfunctions. He specializes in condition monitoring, a technique that uses data from turbine sensors and artificial ...
Mar 14, 2025
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29
Engineering
Korea Institute of Civil Engineering and Building Technology has developed "Generative AI-Based Inspection Technology" to safely construct and maintain urban underground highways.
Mar 11, 2025
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50
Engineering
Scientists say they have developed a new AI-assisted model of a digital twin with the ability to adapt and control the physical machine in real time.
Mar 10, 2025
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