AI-Assisted Digital Twin Could Revolutionize Smart Cities and More

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A breakthrough in digital twin technology could transform how industries such as logistics, healthcare, and defense operate, with the potential to reshape smart cities. Scientists from the University of Sharjah in the UAE have developed a new AI-assisted digital twin model that not only visualizes but also controls physical machines in real time. Published in IEEE Access, the study introduces a concept called Intelligent Acting Digital Twins (IADT), which could dramatically change the way smart systems function and interact with their environments.

Traditionally, digital twins are virtual replicas of physical objects or machines, constantly updated with real-time data. They allow engineers and scientists to monitor and assess the performance of physical assets. However, the new IADT concept takes this a step further by enabling digital twins to autonomously make decisions and control machines without direct human intervention.

The press release gives an example of a scenario where a drone needs to chase an enemy aircraft. In this case, a traditional digital twin would merely simulate different outcomes and offer suggestions. But with IADT, the digital twin would actively control the drone, learning from human pilots and ultimately making independent decisions. This concept could be applied across various industries, including manufacturing, self-driving cars, and healthcare.

The researchers behind this development envision a future where IADTs could manage city infrastructures autonomously, process vast amounts of data, and respond in real-time to emergencies. The system could not only improve efficiency but also enhance emergency response capabilities, disaster management, and public health.

Through testing with the digital twin simulation platform, CupCarbon, the team demonstrated how IADT integrates virtual and physical systems to create a more effective framework for managing real-world applications. The technology could revolutionize sectors that require constant real-time decision-making, from public transportation to defense strategies.

While the advancements offer exciting possibilities, they also raise questions about how autonomous systems might operate in increasingly complex environments, such as smart cities. Will these systems eventually become so sophisticated that human cannot fully grasp how they work? As IADT technology progresses, these concerns will undoubtedly need to be addressed.