Integrating AI and OR for real-time optimization in digital twin ecosystems and metaverse engineering
Abstract
Digital twins are essential in metaverse engineering, serving as a foundation for optimization, simulation, and analysis. However, these digital replicas are vulnerable to malicious software, potentially compromising data and allowing unauthorized access. AI enhances digital twins by enabling them to learn from real-time data, making autonomous decisions. AI algorithms allow for simulating complex environments that react instantly to human input, creating immersive experiences. This article introduces an AI-based study aimed at optimizing digital twin ecosystems and metaverse engineering platforms in real-time (AI-DTE-ME). By integrating metaverse technology with digital twins, realistic and interactive virtual worlds can be created. Continuous data analysis allows digital twins to detect patterns, predict issues, and adapt processes dynamically. This capability brings the Metaverse to life, enabling the creation of intelligent, interactive digital objects. The study highlights the effectiveness of combining AI with operations research (OR) for the real-time optimization of Metaverse engineering and Digital Twin ecosystems.
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