# Digital Twin Framework for Road Infrastructure Management
## 4 Digital Twin Framework for Road Infrastructure Management
### Analysis of Existing DT Frameworks for Road Infrastructure Management
#### 4.1.2 Road Bridges
Cloud servers provide computation and storage capabilities to support data fusion, AI modeling,and big data processing. The HMI component enables access to DT applications and services through application programming interfaces (APIs), web platforms, and related tools. The HMI layer further facilitates data communication, storage, and integration within a common data environment. The human-bridge interaction layer supports comprehensive decision-making based on human expertise or computational outputs. Consequently, digital bridges should be capable of supporting functions such as visualization, monitoring, assessment, simulation, prediction, optimization, reasoning, and collaboration (Figure 4). [PERSON] et al. [9] introduced a DT-based framework for bridge facility management. This framework consists of three main phases: inspection, DT development, and facility management. The first phase, inspection, corresponds to the data acquisition layer of the physical twin and typically involves an automated process that collects accurate and reliable data to lay the foundation for DT modeling. This process enables automatic damage identification with minimal human intervention (e.g., without requiring a site visit). The DT development phase comprises three core components: a BIM model, a damage identification framework, and a data exchange system. The BIM model is automatically generated and semantically enriched, incorporating detailed geometric information. This information includes the original geometry, current structural conditions, updates from inspection data, and visualizations of monitoring results. Furthermore, the bridge DT should support automatic updates of monitoring data and enable integration with complementary models, such as finite element models (FEM), to predict future structural behavior. The facility management stage addresses lifecycle management of the bridge, including structural health monitoring, integration with FEM, and the implementation of optimal intervention strategies. These elements should be incorporated throughout the lifecycle of the bridge to ensure effective facility management. [PERSON] et al. [39] proposed a DT framework integrated with a decision support system to enhance bridge management throughout the entire lifecycle. This conceptual framework comprises six primary layers: monitoring/data collection, data transfer, data processing and storage, DT construction, intelligent decision support, and visualization and automated control. The monitoring/data collection layer gathers bridge inspection data from various sources and tools. These data are then transmitted to a cloud-based IoT database, which serves as the core communication infrastructure for bridge DTs. The  
Figure 4: Interaction among core components of the bridge DT. data processing and storage layer handles large volumes of real-time data using advanced processing techniques to ensure data integrity and accuracy. The DT construction layer incorporates various types of models to represent and analyze bridges. These include 3D surface models that provide detailed representations of the bridge's geometry, simulation-based (FEM) models, data-driven models, and information models. These models are used collectively to simulate, represent, and assess bridge performance. The decision support layer facilitates effective scheduling and prioritization of maintenance tasks through accurate, continuously updated, data-driven procedures. An ideal DT should support the control, monitoring, and optimization of bridge performance, thereby assisting bridge managers and decision-makers in making informed decisions. The outcomes generated by the decision support layer are presented through the UI layer. This layer translates analytical results into an easily understandable format, enabling stakeholders to derive insights with minimal effort. [PERSON] et al. [42] presented a BIM-based DT model designed to support bridge management throughout the entire lifecycle.