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Digital Twin technology revolutionizes urban transportation by creating virtual models of physical infrastructure. This technology integrates real-time data from various sources, enabling better planning, operation, and maintenance of transportation assets. The study highlights the potential of Digital Twins to enhance traffic flow simulation and predictive maintenance strategies.
Despite its advantages, the adoption of Digital Twin technology faces challenges such as data integration and real-time processing demands. The study emphasizes the need for a holistic approach to embed Digital Twins across all phases of infrastructure management. Future advancements in AI, IoT, and cloud computing are expected to facilitate widespread adoption and improve urban transportation systems.
• Digital Twin technology enhances urban transportation management through real-time data integration.
• AI-driven predictive analytics can improve maintenance planning and reduce infrastructure failures.
Digital Twin technology creates virtual representations of physical assets for enhanced management.
Predictive analytics uses data to forecast future events, improving decision-making in infrastructure.
IoT refers to interconnected devices that collect and exchange data, crucial for real-time monitoring.
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