Effective civil infrastructure management necessitates the utilization of timely data across the entire asset lifecycle for condition assessment and predictive maintenance. A notable gap in current predictive maintenance practices is the reliance on single-source data instead of heterogeneous data, decreasing data accuracy, reliability, adaptability, and further effectiveness of engineering decision-making. Data fusion is thus demanded to transform low-dimensional decisions from individual sensors into high-dimensional ones for decision optimization. In this context, digital twin (DT) technology is set to revolutionize the civil infrastructure industry by facilitating real-time data processing and informed decision-making. However, data-driven smart civil infrastructure management using DT is not yet achieved, especially in terms of data fusion. This paper aims to establish a conceptual framework for harnessing DT technology with data fusion to ensure the efficiency of civil infrastructures throughout their lifecycle. To achieve this objective, a systematic review of 105 papers was conducted to thematically analyze data fusion approaches and DT frameworks for civil infrastructure management, including their applications, core DT technologies, and challenges. Several gaps are identified, such as the difficulty in data integration due to data heterogeneity, seamless interoperability, difficulties associated with data quality, maintaining the semantic features of big data, technological limitations, and complexities with algorithm selection. Given these challenges, this research proposed a framework emphasizing multilayer data fusion, the integration of open building information modeling (openBIM) and geographic information system (GIS) for immersive visualization and stakeholder engagement, and the adoption of extended industry foundation classes (IFC) for data integration throughout the asset lifecycle.

In recent years, the implementation of digital twin (DT) technology has gained significant attention in various industries. However, the fire safety management (FSM) sector has been relatively slow in adopting this technology compared to other major industries. Therefore, this study aims to explore the limitations, opportunities, and challenges associated with adopting DT technology in the FSM sector and further develop a DT-based FSM framework towards smart facility management (FM). To achieve this objective, this research started by reviewing several promising DTs for FSM, including building information modeling (BIM), the Internet of Things (IoT), artificial intelligence (AI), and augmented reality (AR). On this basis, a conceptual framework was synthesized in consideration of the benefits of each technology. A questionnaire was conducted for FM professionals to evaluate the proposed framework and identify the challenges of adopting DT in the FSM sector. The survey results reveal that the proposed framework can assist decision makers in obtaining comprehensive information about facilities’ communication among stakeholders. The survey results validate the potential of the adoption of DTs toward smart FM practices in FSM. The survey results provide insights into the perception of DT technology among FM practitioners and identify the current state of DT technology in the FSM sector, its expected benefits, and its potential challenges. The main barriers to adopting DTs in FSM are a lack of knowledge about DTs, their initial costs, user acceptance, difficulties in systems integration, education training costs, a lack of competence, development complexity, difficulties in data management, and a lack of trust in data security.

External human–machine interfaces (eHMIs) serve as communication bridges between autonomous vehicles (AVs) and road users, ensuring that vehicles convey information clearly to those around them. While their potential has been explored in one-to-one contexts, the effectiveness of eHMIs in complex, real-world scenarios with multiple pedestrians remains relatively unexplored. Addressing this gap, our study provides an in-depth evaluation of how various eHMI displays affect pedestrian behavior. The research aimed to identify eHMI configurations that most effectively convey an AV’s information, thereby enhancing pedestrian safety. Incorporating a mixed-methods approach, our study combined controlled outdoor experiments, involving 31 participants initially and 14 in a follow-up session, supplemented by an intercept survey involving 171 additional individuals. The participants were exposed to various eHMI displays in crossing scenarios to measure their impact on pedestrian perception and crossing behavior. Our findings reveal that the integration of a flashing green LED, robotic sign, and countdown timer constitutes the most effective eHMI display. This configuration notably increased pedestrians’ willingness to cross and decreased their response times, indicating a strong preference and enhanced concept understanding. These findings lay the groundwork for future developments in AV technology and traffic safety, potentially guiding policymakers and manufacturers in creating safer urban environments.

Understanding the process of concrete bridge deck deterioration and evaluating its condition in an accurate and reliable manner could help bridge owners to better plan for allocating the funds for bridge maintenance, rehabilitation, or reconstruction actions. Therefore, it is very important to investigate the factors impacting the bridge condition. The main objective of this paper is to study the impact of environmental factors on the concrete bridge deck deterioration. National bridge condition from over 25 years of data were analyzed to determine the impact of environmental factors on concrete decks. The U.S. map was divided into six different climatic regions that were used as the basis for the environmental impact study. This study has revealed that environmental factors have a significant effect on the deterioration of concrete bridge decks.