Digital Twins and Data-Driven Infrastructure Management

Digital twins represent transformative technology for decarbonized transport infrastructure management, integrating real-time data analytics, artificial intelligence, and predictive modeling. This chapter examines the convergence of digital twin technology and data-driven decision-making in sustainable transportation systems, exploring economic implications, market mechanisms, and policy innovations driving decarbonization. Through comprehensive analysis of current applications, technological frameworks, and implementation strategies, this work demonstrates how digital twins enable optimized infrastructure performance, reduced carbon emissions, and enhanced operational efficiency. Key findings reveal that integrating AI-powered digital twins with IoT sensors, machine learning algorithms, and cloud computing platforms creates intelligent transportation systems capable of real-time monitoring, predictive maintenance, and adaptive control.

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