Technological Innovations in Sustainable Civil Engineering: Advanced Materials, Resilient Design, and Digital Tools

Biopharma Is Going Digital … Bit by Bit

The present study uses a bibliometric and systematic literature review (SLR) to examine the use of Building Information Modeling (BIM), the Internet of Things (IoT), and Digital Twins (DT) in the construction industry. The network visualization and other approaches based on the Web of Science (WOS) database and the patterns of research interactions were explored in 1879 academic publications using co-occurrence and co-citation investigations. Significant publications, conferences, influential authors, countries, organizations, and funding agencies have been recognized. Our study demonstrates that BIM, IoT, and DT in construction, Heritage BIM (HBIM), Smart Contracts, BIM, and Ontology, and VR and AR in BIM and DT are the main study themes. Finally, several prospective areas for future study are identified, including BIM and Metaverse technology, BIM and Artificial Intelligence (AI), Metaheuristic algorithms for optimization purposes in BIM, and the Circular Economy with BIM and IoT.

Abstract. Technology has advanced and progressed tremendously, and the term city is being elevated to a new level where the smart city has been introduced globally. Recent developments in the concept of smart city have led to a renewed interest in Digital Twin. Using precise Building Information Modelling (BIM) consolidated with big data and sensors, several attempts have been made to establish digital twin smart cities. In recent years, several researchers have sought to determine the capability of smart city and digital twin for various taxonomies such as development and urban planning purposes, built environment, manufacturing, environmental, disaster management, and healthcare. Despite being beneficial in many disciplines, especially in manufacturing, built environment, and urban planning, these existing studies have shown a lack of aspect in terms of emergency or disaster-related as opposed to the elements mentioned above. This is because the researcher has not treated emergencies or disasters in much detail. Therefore, an extensive review on smart city, digital twin, BIM and disaster management and technology that revolves around these terms were summarised. In general, 39 articles from prominent multidisciplinary databases were retrieved over the last two decades based on the suggested PRISMA workflow. These final articles were analysed and categorised into four themes based on the research content, gist, and keywords. Based on the review of 39 articles related to smart city, digital twin and BIM, a workflow for the smart city digital twin and the conceptual framework for indoor disaster management was proposed accordingly. The establishment of smart city digital twins solely for an indoor emergency can be beneficial to urbanites, and it could provide numerous benefits for enhanced situation assessment, decision making, coordination, and resource allocation.

This systematic review and meta-analysis investigates the evolving role of Building Information Modeling (BIM) in managing multidimensional risks associated with sustainable bridge infrastructure projects. Drawing upon the PRISMA methodology, the study rigorously screened and analyzed a total of 87 peer-reviewed journal articles and conference papers published between 2010 and 2024. The selected literature was sourced from five leading academic databases—Scopus, Web of Science, IEEE Xplore, ScienceDirect, and the ASCE Library—ensuring comprehensive coverage of global research on BIM-based risk management practices. The review focuses on how BIM contributes to the identification, analysis, mitigation, and continuous monitoring of technical, financial, environmental, and operational risks throughout the lifecycle of bridge projects. Findings reveal that BIM’s capabilities extend well beyond 3D visualization, offering robust tools for 4D scheduling, 5D cost estimation, and real-time data integration that collectively enhance proactive decision-making. BIM facilitates early risk detection through clash detection, geospatial analysis, and scenario simulations during the planning and design stages, reducing design inconsistencies and constructability issues. Moreover, the study synthesizes evidence demonstrating how BIM supports cost and schedule risk control by enabling dynamic simulation of construction sequences and integration with live pricing data, resulting in reduced cost overruns and schedule delays. The review also highlights the increasing convergence of BIM with Internet of Things (IoT) technologies, digital twins, and Geographic Information Systems (GIS), enabling real-time monitoring of structural health, predictive maintenance, and environmental risk modeling in operational phases. Lifecycle-oriented risk governance through BIM emerged as a key theme, particularly in studies focused on sustainability assessments, material optimization, and long-term asset performance. Institutional adoption patterns, regulatory influences, and policy frameworks were also examined, revealing that countries with mandated BIM protocols exhibit more advanced integration of BIM into public infrastructure risk management. Despite persistent challenges such as fragmented data standards, skill gaps, and limited interoperability, the majority of the reviewed literature—accumulating over 3,400 citations—converges on the conclusion that BIM is an essential enabler of risk-informed, sustainable bridge engineering.

Purpose This study proposes a phased digital twin framework aimed at enhancing construction management and procurement efficiency in smart infrastructure projects. The framework integrates building information modeling (BIM), Internet of Things (IoT) sensors and predictive analytics to facilitate real-time decision-making across the design, execution and procurement phases. Design/methodology/approach Using structural equation modeling (SEM) for data analysis, the study establishes causal relationships between digital twin adoption and improvements in procurement lead time, resource utilization and cost predictability. Findings The findings underscore the significance of phased implementation, highlighting that incremental adoption leads to more sustainable outcomes and organizational learning. Practical implications Digital twin (DT) technology is emerging as a transformative force in the construction industry, enabling real-time data integration, predictive analysis and lifecycle optimization. However, its application in construction management and procurement remains fragmented, particularly in emerging markets where infrastructure expansion is rapid but constrained by inefficiencies. This research contributes to the construction management literature by offering a structured digitalization roadmap and aligning operational practices with the Sustainable Development Goals (SDGs). Originality/value No previous Studies on digital twins relating to construction management and procurement efficiency is done to ours knowledge.

This study investigated how Building Information Modeling (BIM) and Digital Twin (DT) technologies influenced risk reduction in civil infrastructure projects using a cross-sectional quantitative design. The dataset comprised 168 civil infrastructure projects across highways (36.9%), bridges (24.4%), rail corridors (19.6%), tunnels (10.7%), and water infrastructure (8.3%), delivered through design–bid–build (39.9%), design–build (32.1%), and PPP/alliance procurement (28.0). Digital implementation showed mid-to-high BIM practice (BIM adoption intensity M = 3.74, SD = 0.71; BIM maturity M = 3.58, SD = 0.68) and more dispersed DT practice (DT utilization M = 3.12, SD = 0.89; DT predictive capacity M = 3.26, SD = 0.84), while integration maturity remained moderate (M = 3.41, SD = 0.79). Risk reduction outcomes demonstrated substantial variability (cost risk reduction M = 64.8, SD = 12.5; schedule M = 61.3, SD = 13.9; safety M = 55.7, SD = 15.6; quality M = 59.9, SD = 14.2; operational M = 67.2, SD = 11.8; composite index M = 61.8, SD = 10.7). Correlations were positive across domains, with integration maturity showing the strongest association with the composite risk index (r = 0.61). Reliability and validity were adequate for all constructs (Cronbach’s alpha 0.81–0.89, composite reliability 0.86–0.92, AVE 0.53–0.64), and collinearity remained acceptable (VIF 1.20–2.27). Hierarchical regression indicated that BIM predictors explained the largest incremental variance in cost and schedule risk reduction (ΔR² = 0.18–0.20), DT predictors contributed most to safety and operational risk reduction (ΔR² = 0.15–0.22), and integration maturity added broad multi-risk explanatory power, especially for the composite index (ΔR² = 0.14, β = 0.41, p < .001). Moderation tests showed complexity weakened BIM scheduling effects, whereas data reliability and team digital capability strengthened DT and integration impacts. Overall, BIM stabilized delivery risks, DTs strengthened safety and operational reliability, and BIM–DT integration yielded the most comprehensive multidimensional risk reduction.

The idea of a smart city has evolved in recent years from limiting the city’s physical growth to a comprehensive idea that includes physical, social, information, and knowledge infrastructure. As of right now, many studies indicate the potential advantages of smart cities in the fields of education, transportation, and entertainment to achieve more sustainability, efficiency, optimization, collaboration, and creativity. So, it is necessary to survey some technical knowledge and technology to establish the smart city and digitize its services. Traffic and transportation management, together with other subsystems, is one of the key components of creating a smart city. We specify this research by exploring digital twin (DT) technologies and 3D model information in the context of traffic management as well as the need to acquire them in the modern world. Despite the abundance of research in this field, the majority of them concentrate on the technical aspects of its design in diverse sectors. More details are required on the application of DTs in the creation of intelligent transportation systems. Results from the literature indicate that implementing the Internet of Things (IoT) to the scope of traffic addresses the traffic management issues in densely populated cities and somewhat affects the air pollution reduction caused by transportation systems. Leading countries are moving towards integrated systems and platforms using Building Information Modelling (BIM), IoT, and Spatial Data Infrastructure (SDI) to make cities smarter. There has been limited research on the application of digital twin technology in traffic control. One reason for this could be the complexity of the traffic system, which involves multiple variables and interactions between different components. Developing an accurate digital twin model for traffic control would require a significant amount of data collection and analysis, as well as advanced modeling techniques to account for the dynamic nature of traffic flow. We explore the requirements for the implementation of the digital twin in the traffic control industry and a proper architecture based on 6 main layers is investigated for the deployment of this system. In addition, an emphasis on the particular function of DT in simulating high traffic flow, keeping track of accidents, and choosing the optimal path for vehicles has been reviewed. Furthermore, incorporating user-generated content and volunteered geographic information (VGI), considering the idea of the human as a sensor, together with IoT can be a future direction to provide a more accurate and up-to-date representation of the physical environment, especially for traffic control, according to the literature review. The results show there are some limitations in digital twins for traffic control. The current digital twins are only a 3D representation of the real world. The difficulty of synchronizing real and virtual world information is another challenge. Eventually, in order to employ this technology as effectively as feasible in urban management, the researchers must address these drawbacks.

With various emerging technologies and integration possibilities, smart facility management has gained wide interest in recent years. Several technologies were introduced to support facilities management and improve decision-making, such as Building Information Modeling (BIM), Internet of Things (IoT), Digital Twin (DT), artificial intelligence (AI), and blockchain. Yet, facility managers still face challenges related to data handling and the actual implementation of these technologies. Thus, this paper explores the trends and integration possibilities of smart facilities management technologies to provide a deeper understanding of the current research state and the areas for future exploration. The Scopus database is utilized to collect literature data, and a bibliometric analysis is conducted on 7236 publications of different types, including conference publications, articles, reviews, and book chapters, using VOSviewer software. The results revealed a noticeable growth in the annual number of publications related to this field after 2018. BIM, IoT, and DT were seen to share the greatest research attention, with BIM being the dominant technology. With recent wide attention, blockchain technology is noticed to be introducing many integration possibilities. In addition, the prominent contributing authors, countries, and sources to this research area are also identified.

The digital twin is becoming increasingly popular for building operation management with the support of building information modeling (BIM) applications and the Internet of Things (IoT). However, current research of the BIM and IoT supported digital twin platform often focuses on specific building operation tasks and lacks consideration of the implication challenges. This study investigates the potential application and characteristics of the digital twin platform in building operation management and the root issues that prohibit the implementation of the digital twin platform. The supporting roles of BIM and IoT in the potential application are also discussed. The literature analysis is conducted to identify the success factors from the recent paper on digital twin applications. The potential opportunities and challenges are summarized and analyzed following the proposed framework. This study hopes to guide the development of the BIM and IoT supported digital twin platform toward a practical platform for improving building operation.

This paper systematically maps how digital transformation technologies associated with Industry 4.0 (I4.0) are conceptualised in relation to concerns within the built environment regarding sustainability. Employing a hybrid methodology that combines scoping review, bibliometric mapping, and thematic analysis, an initial corpus of 1513 documents from Web of Science and Scopus was refined to 83 influential peer-reviewed publications. The analysis identified thirteen key I4.0 technologies for sustainability in the built environment that are frequently discussed, including Building Information Modelling (BIM), Digital Twins (DT), Internet of Things (IoT), Blockchain, Artificial Intelligence (AI), and others, each demonstrating varying degrees of explicit sustainability relevance. Notably, the study uncovered recurrent combinations, or "technology stacks", such as BIM integrated with DT and IoT, or Blockchain combined with BIM and IoT, which significantly enhance sustainability outcomes through interoperability and functional synergies. Despite these findings, substantial conceptual fragmentation and inconsistent terminology were noted across the literature, limiting theoretical coherence and empirical validation. The study highlights the importance of standardised taxonomies and comprehensive empirical studies to rigorously validate technology stacks and their sustainability impacts across diverse built environment contexts.

The current practice of Architecture, Engineering, and Construction (AEC) management systems relies on time-consuming, manual methods for data collection, analyzing, and decision-making. This affects the productivity of the industry in all phases: design, construction, operation, and maintenance of their assets. Adoption of innovative technologies is the key solution for the AEC industry to overcome the challenges they face and follow other reinvented industries. Although recent advancements have been proposed for more productive data acquisition and decision support by leveraging digital tools, Building Information Modeling (BIM), Internet of Things (IoT), and Artificial Intelligence (AI), the fragmented approach of adoption and the absence of a connected workflow is a barrier. Digital Twin (DT) is a digital presentation of a physical entity that replicates the status and behavior of its physical counterpart. It can help to improve overall system effectiveness and reliable data-informed decisions. However, the concept of DT and its key features is still not well-understood in the AEC industry. Therefore, this paper aims to review and investigate the twinning requirements and characteristics of DT and discuss its structure and potential solutions in terms of AEC infrastructure and buildings assets operations and maintenance systems. The DT concept, main characteristics, and critical considerations for the AEC sector are highlighted and classification for DT levels is introduced and discussed.

Towards digital architecture, engineering, and construction (AEC) industry through virtual design and construction (VDC) and digital twin

A digital twin (DT) system is a virtual system that can provide a comprehensive description of a real physical system. The DT system continuously receives data from physical sensors and user input information and provides information feedback to the physical system. It is an emerging technology that utilizes an advanced Internet of Things (IoT) to connect different objects, which is in high demand in various industries and its research literature is growing exponentially. Traditional physical systems provide data support for the monitoring of physical objects such as buildings through digital modeling techniques, data acquisition tools, human computer interfaces, and building information models (BIM). However, DT can offer much more than data presentation. DT uses the received data to perform operations such as analysis, prediction, and simulation, and finally transmits the analysis results to the physical system as feedback. Compared with other physical systems, DT has the characteristics of bidirectional data exchange and real-time autonomous management. The plant factory control system based on digital twin technology continuously measures the power consumption of electrical equipment through the sensors of the physical system and makes the corresponding virtual color-coded gradient map based on the obtained data. The darker the virtual device is, the more power it currently requires, and just based on the shade of color gives the user a very intuitive idea of the current power usage of the electronic device. There has been extensive research on digital twin technology, but there are few studies on implementing plant factories based on digital twin technology. This paper proposes the idea of combining digital twin technology with plant factories to provide research directions for future smart agriculture. It proves that smart agricultural production with sustainability can also benefit from this idea.

Purpose This paper aims to fill the research gap on digital twin technology and its broad applicability during construction by shedding light on its interaction with Building Information Modeling (BIM) from a construction project management perspective. It presented the true potential of the digital twins in the construction phase of the project lifecycle. Design/methodology/approach The paper employed a two-step methodology that included a comprehensive synthesis of the literature on digital twins through the construction management lens and a questionnaire survey to assess the impact of digital twin services brought to light on parallel BIM uses. Findings The paper provides validated applications and many advantages of the digital twin on construction project management. It suggests that the industry should take advantage of 10 digital twin services introduced to eliminate the low efficiency and lack of productivity that the construction industry is still facing. Research limitations/implications The paper is one of the rare and pioneering studies that addresses the interaction between the digital twin and BIM from a construction management perspective with a quantitative approach examining the reflection of academic publications on the industry and their reception among industry professionals. Practical implications The paper provides a meaningful definition for the industry by grounding the concept of digital twin in existing technologies and their practical applications. This provides a roadmap for managers to approach the problems and BIM limitations they need to overcome in their companies or projects with tailor-made solutions. Originality/value The paper is one of the pioneering quantitative studies that fulfills an identified need to investigate digital twin technology for construction management and its extensive applicability for quickly evolving construction sites.

As COVID-19 strained health systems around the world, many countries developed or adapted digital health tools to detect and respond to the novel coronavirus. We identified transferable lessons from an assessment of implementation factors that led to the rapid launch and scale-up of eight digital tools in low- and middle-income countries during the COVID-19 pandemic. These lessons should inform the development of digital health tools to support public health objectives such as the Sustainable Development Goals. Using the mHealth Assessment and Planning for Scale Toolkit, we assessed the implementation of eight digital tools through desk research and stakeholder interviews. Three core lessons emerged from our findings: (1) user-centered design is key to the widespread adoption of digital tools; (2) strong, country-led partnerships are essential for scaling up and sustaining digital tools; and (3) using adaptable digital tools enables implementers to focus on the content of the solution rather than the technology. Lessons learned from implementing and adapting digital tools quickly during the COVID-19 pandemic can inform the use of digital tools for additional health applications, such as bolstering primary health care, reaching vulnerable and marginalized populations, and empowering health workers with the real-time information necessary to optimize their work and improve the health of their target populations. Future efforts should focus on robust monitoring and evaluation of digital tools and sustainable financing models.