Modern infrastructure systems generate large volumes of data through sensing technologies, monitoring platforms, and digital engineering tools. However, the availability of data alone does not ensure improved infrastructure performance, resilience, or sustainability. A key challenge lies in systematically transforming heterogeneous data into actionable decisions that support real-time operation and long-term infrastructure management. Despite advances in Internet of Things (IoT), artificial intelligence (AI), and digital twins (DTs), existing implementations often remain fragmented, with limited integration between data acquisition, analytical modeling, and operational decision processes. This study proposes a decision-centric framework for intelligent and sustainable infrastructure systems, in which data, analytics, and digital twins are explicitly organized to support engineering decision-making. The framework is formalized through a data–digital twin decision (DTTD) architecture that defines data flows, analytical models, and decision mechanisms within a closed-loop system. A five-layer architecture is developed that integrates sensing systems, data platforms, AI-driven analytics, digital twin environments, and operational decision processes. The framework is validated through a tunnel engineering case study and further generalized across transportation, energy, and flood management systems using a structured analytical mapping of data inputs, models, and decision variables. The results demonstrate improved decision consistency, enhanced responsiveness to changing conditions, and more efficient operational management within the case study context. The findings highlight that the value of digital infrastructure lies not in data generation alone, but in its ability to support timely, reliable, and adaptive decision-making. The proposed framework provides a transferable methodological foundation for implementing decision-centric infrastructure systems, contributing to the development of resilient and sustainable urban environments.
Tuan A. Pham (Wed,) studied this question.