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There has been a plethora of research on the performance of schedule and cost in construction projects. However, current research falls short in investigating the combined contribution of different construction technologies on project performance metrics. Specifically, none of the previous efforts have used integrated earned value management (EVM) parameters and utilized construction technologies to assess project schedule and cost performance. This paper fills this knowledge gap. To this end, a multistep research methodology was employed to (1) explore the utilization ratings of 13 construction technologies based on data collected from 52 industry experts; (2) rank these technologies in terms of their contribution to schedule and cost savings; (3) map the utilization ratings of construction technologies to schedule and cost variances by leveraging data from 48 construction projects with varying levels and scopes of technology integration to gauge the impact of using these technologies; and (4) develop an associated decision-support model that underwent rigorous verification under extreme conditions and sensitivity analysis. This study makes a noteworthy contribution to the existing body knowledge, revealing that the major drivers for schedule savings are building information modeling (BIM), unmanned aerial vehicles (UAVs), and augmented/virtual reality (AR/VR), while additive manufacturing (AM), digital twin (DT), and Internet of Things (IoT) are the most significant contributors to cost savings. Moreover, the study reveals strong correlations between various technologies, such as UAVs and laser scanning, geographic information system (GIS) and GPS, AR/VR and digital twins, as well as robotics/automation and AR/VR. Furthermore, the study introduces a novel model that enhances the prediction of project performance, specifically in terms of schedule and cost variations resulting from the adoption of various construction technologies. Eventually, it improves the decision-making process related to the deployment of the investigated construction technologies. [ABSTRACT FROM AUTHOR]

Engineer-to-order manufacturing, characterized by highly customized products and complex workflows, presents unique challenges for warehouse management and operational efficiency. This paper explores the potential of a digital twin as a transformative solution for engineer-to-order environments in manufacturing companies realizing prefabricated building components. This paper outlines a methodology encompassing users' requirements and the design to support the development of a digital twin that integrates Internet of Things devices, Building Information Modeling, and artificial intelligence capabilities. It delves into the specific challenges of outdoor warehouse optimization and worker safety within the context of engineer-to-order manufacturing, and how the digital twin aims to address these issues through data collection, analysis, and visualization. The research is conducted through an in-depth analysis of the warehouse of Focchi S.p.A., a leading manufacturer of high-tech prefabricated building envelopes. Focchi's production processes and stakeholder interactions are investigated, and the paper identifies key user groups and their multiple requirements for warehouse improvement. It also examines the potential of the digital twin to streamline communication, improve decision-making, and enhance safety protocols. While preliminary testing results are not yet available, the paper concludes by underlining the significant opportunities offered by a BIM-, IoT-, and AI-powered digital twin for engineer-to-order manufacturers. This research, developed within the IRIS project, serves as a promising model for integrating digital technologies into complex warehouse environments, paving the way for increased efficiency, safety, and ultimately, a competitive edge in the market of manufacturing companies working in the construction industry. [ABSTRACT FROM AUTHOR]

Historic Building Information Modelling (HBIM) plays a pivotal role in heritage conservation endeavours, offering a robust framework for digitally documenting existing structures and supporting conservation practices. However, HBIM's efficacy hinges upon the implementation of case-specific approaches to address the requirements and resources of each individual asset and context. This paper defines a flexible and generalisable workflow that encompasses various aspects (i.e., documentation, surveying, vulnerability assessment) to support risk-informed decision making in heritage management tailored to the peculiar conservation needs of the structure. This methodology includes an initial investigation covering historical data collection, metric and condition surveys and non-destructive testing. The second stage includes Finite Element Method (FEM) modelling and structural analysis. All data generated and processed are managed in a multi-purpose HBIM model. The methodology is tested on a relevant case study, namely, the church of Santa Ana in Seville, chosen for its historical significance, intricacy and susceptibility to seismic action. The defined level of detail of the HBIM model is sufficient to inform the structural analysis, being balanced by a more accurate representation of the alterations, through linked orthophotos and a comprehensive list of alphanumerical parameters. This ensures an adequate level of information, optimising the trade-off between model complexity, investigation time requirements, computational burden and reliability in the decision-making process. Field testing and FEM analysis provide valuable insight into the main sources of vulnerability in the building, including the connection between the tower and nave and the slenderness of the columns. [ABSTRACT FROM AUTHOR]

This article presents a case study with various developments of digital twinning of a sample of load tests performed on several railways bridges. The case study is located in Extremadura, South Western Spain and its aim is the generation of a validated, multi-layered information construct in the form of a digital twin as the result of a load test. This result is conceived, not only to verify the assumptions of the design of the bridge but also, to optimize future maintenance plans of the network. This particular case study is framed within a vaster European effort on digitization of the construction sector. Research and Innovation Actions within this demo case are aimed at integrating routine requirements and procedures of load tests with cutting edge digital technologies for the generation of validated virtual replica of these physical bridges. The generated twins during these load tests behaviourally match the obtained response during loading and as such, represent an ideal model for future simulations and behavioural predictions. Different data-gathering techniques and numerical models are integrated within a Common Data Environment (CDE). All efforts related to measurement, simulation, 3D modelling, assessment and validation can be wrapped up systematically for further use during regular operation of the asset. [ABSTRACT FROM AUTHOR]

This article presents a model built for deep digitalization in the construction industry and for making building information modeling achieve a greater level of transparency, verifiability and effectiveness for the benefit of all stakeholders. Thanks to blockchain and the self-sovereign identity paradigm, the model guarantees data integrity and transaction reliability, enabling the generation of more efficient and productive businesses. The model includes a decentralized application for notarization of the information flow in building information modeling processes; the application is implemented and tested on a local blockchain. The proposed model represents a so-called digital twin and is, hence, a huge system that manages all the information flow associated with a building throughout its life cycle, returning to individuals the control of their own data. In this model, all stakeholders operate based on so-called decentralized identifiers and DID documents, which store on-chain the fingerprints of the information flow in a common data environment. [ABSTRACT FROM AUTHOR]

Modern building automation systems implement plenty of advanced control and monitoring functions that consider various parameters like users' activity, lighting, temperature changes, etc. Moreover, novel solutions based on the Internet of Things and cloud services are also being developed for smart buildings to ensure comfort of use, user safety, energy efficiency improvements, and integration with smart grids and smart city platforms. Such a wide spectrum of technologies and functions requires a novel approach in building automation systems design to provide effective implementation and flexibility during operation. At the same time, in the building design and operation industries, tools based on building information modeling and digital twins are being developed. This paper discusses the development directions and application areas of these solutions, identifying new trends and possibilities of their use in smart homes and buildings. In particular, the focus is on procedures for selecting automation functions, effective integration, and interoperability of building management systems with the Internet of Things, considering the organization of prediction mechanisms and dynamic functional changes in buildings and smart networks. Chosen solutions and functions should consider the requirements set out in the EN ISO 52120 standard and the guidelines defined for the Smart Readiness Indicator. [ABSTRACT FROM AUTHOR]

The construction industry's reliance on traditional methods and fragmented workflows results in significant information loss, inefficiencies, increased costs, and errors. This study addresses these issues by integrating comprehensive urban planning with building information modeling (BIM) to create a seamless information flow throughout the building lifecycle. We propose a holistic framework that synchronizes data from planning to demolition, incorporating national and municipal digital twins. An imperative literature review and analysis of international best practices were conducted to develop a conceptual framework aimed at improving data accuracy and interoperability. Our findings underscore the importance of adopting open standards such as Industry Foundation Classes (IFC) and CityGML for effective information exchange. By implementing an information model (IM)-based approach in urban planning and public sector permit processes, project timelines can be streamlined, and regulatory compliance enhanced. This study concludes that continuous, integrated information flow facilitates more efficient, cost-effective construction practices and improved decision-making. Furthermore, this research illustrates the potential of digital twin technology to revolutionize the construction industry by enabling real-time data integration and fostering stakeholder collaboration, ultimately offering a robust framework for practitioners, and significantly enhancing the efficiency and accuracy of construction processes. [ABSTRACT FROM AUTHOR]

In a construction project schedule, delays in delivery are one of the most important problems. Delays can be caused by several project components; however, the issue is amplified when delays occur simultaneously. Classifying delays is relevant in order to allocate responsibility to the parties. In Italy, the delay in the delivery of medium and large-sized works in residential urban centers is about 15% compared to the project forecast. Moreover, the AECO sector's ability to adapt to emerging challenges, such as environmental sustainability and digitization, is limited by the lack of innovation in management methods. The aim of this research is to create a methodology for managing the built and to-be-built environment in a digital way. This will optimize the building process by reducing delays and waste of resources. The methodology will use tools such as digital twin (DT), Building Information Modeling (BIM), Internet of Things (IoT), and Artificial Intelligence (AI) algorithms. The integration of lean construction practices can make the use of these technologies even more efficient, supporting better workflow management by using the BIM environment. The paper presents a methodology that can be applied to various scaling factors and scenarios. It is also useful for construction sites that are already in progress. As highlighted below, this brings significant economic-temporal advantages. [ABSTRACT FROM AUTHOR]

Building Information Modelling (BIM) has emerged as a transformative force in the construction industry, gaining traction within the hydropower sector. This study critically examines the adoption and application of BIM throughout the entire lifecycle of hydropower projects, addressing a notable gap in existing research, to encompass a holistic approach to the management and resilience of these critical infrastructures. The objective is to delineate the comprehensive range of BIM applications, use cases, and adoption, integrating technologies including Digital Twin, UAV, GIS, and simulation tools, across components of hydropower projects. Employing a systematic search paired with a critical review of the selected literature, this study meticulously evaluates significant contributions in this domain. Through thematic analysis, the multifaceted utility of BIM in hydropower structures, including an in-depth evaluation of its current adoption within the industry, is presented. This encompasses an analysis of both benefits and challenges inherent in BIM implementation for hydropower infrastructures. This study is a significant contribution to understanding how BIM can be leveraged to enhance the resilience of hydropower infrastructures. It provides a comprehensive view of BIM's applications, challenges, and future potential, guiding stakeholders in adopting strategies that ensure these structures withstand, adapt, and recover from disruptions while maintaining sustainable and efficient operations. [ABSTRACT FROM AUTHOR]

The growing interest in building data management, especially the building information model (BIM), has significantly influenced urban management, materials supply chain analysis, documentation, and storage. However, the integration of BIM into 3D GIS tools is becoming more common, showing progress beyond the traditional problem. To address this, this study proposes data transformation methods involving mapping between three domains: industry foundation classes (IFC), city geometry markup language (CityGML), and web ontology framework (OWL)/resource description framework (RDF). Initially, IFC data are converted to CityGML format using the feature manipulation engine (FME) at CityGML standard's levels of detail 4 (LOD4) to enhance BIM data interoperability. Subsequently, CityGML is converted to the OWL/RDF diagram format to validate the proposed BIM conversion process. To ensure integration between BIM and GIS, geometric data and information are visualized through Cesium Ion web services and Unreal Engine. Additionally, an RDF graph is applied to analyze the association between the semantic mapping of the CityGML standard, with Neo4j (a graph database management system) utilized for visualization. The study's results demonstrate that the proposed data transformation methods significantly improve the interoperability and visualization of 3D city models, facilitating better urban management and planning. [ABSTRACT FROM AUTHOR]

The rapid growth of technology worldwide in different ways drives the construction sector to take the same path. Smart cities, Digital Twins, Building Information Modeling (BIM), and the Internet of Things (IoT) are the trends in this way today. Also, integrating Building Information Modeling (BIM) and Internet of Things (IoT) technologies has revolutionized how buildings are designed, constructed, maintained, and managed. On the other hand, the complexity, high cost, need for expertise, and other things make the maintenance process and facility management by human inspections, commercial software, and different tools not suitable for the growth of the technology. This paper presents a proposal for a workflow of integration between BIM, and an algorithm of Maintenance System with IoT and highlights its potential to enhance building performance and facility management. The paper explores this innovative system's underlying principles, benefits, challenges, and implementation strategies. Furthermore, it discusses the implications of BIM, and the proposed algorithm of Maintenance System with IoT integration on various stakeholders, including building owners, facility managers, and occupants by using a case study. The findings collected by a questionnaire for some experts emphasize the importance of adopting this integrated approach to optimize building operations, improve maintenance practices, and create sustainable and intelligent built environments. [ABSTRACT FROM AUTHOR]

Implementing circular economy principles in the built environment significantly reduces raw material extraction and generated waste. A transition is essential, especially as it accounts for 40-60% of global raw material extraction and 33% of total waste in the European Union. This paper shows the methodological approach to generating a digital Building model to enable circular economy in the early design stage by coupling Generative Design methods, enabling automated variant generation of Digital building models, Building Information Modelling objects, and assessment algorithms to evaluate the environmental impact and circularity. By visualising the assessments of the generated variants of (so-called) Circular Twins in a Virtual Reality environment, including user interaction with a voice-controlled Virtual Agent, the digital Circular Twin ecosystem enables the early implementation of the goals of the circular economy and sustainability in Architecture, Engineering and Construction. [ABSTRACT FROM AUTHOR]

Building energy system management is critical for resource-saving approaches amid climate change-driven energy transitions. This paper presents a digital twin toolchain leveraging modern technologies such as Building Information Modeling (BIM), Artificial Intelligence (AI), Virtual Reality (VR), and Augmented Reality (AR). The toolchain automates the derivation of georeferenced digital twins during Technical Building Equipment (TBE) commissioning. Using a Scan vs. BIM process, discrepancies between as-planned and as-built TBE are identified, allowing automatic updates to the BIM model. Validation methods ensure both physical and functional aspects of the TBE are accurate. VR and AR facilitate off- and on-site commissioning, enabling immersive visualization and live sensor data access. An evaluation in small and large-scale demonstrators shows the toolchain's scalability and efficiency, with promising results in performance and accuracy. Future work aims to integrate more operational data, enhancing the digital twin's capabilities for building energy system management. [ABSTRACT FROM AUTHOR]

This paper delves into the integration of Factories of the Future (FoF) and digital twin technologies within urban contexts, marking a significant leap in Smart Cities development. We present a thorough exploration of the principles and a scientifically grounded framework designed for seamlessly blending advanced manufacturing systems with the urban environment's digital and physical aspects. Our detailed analysis has identified core principles crucial for this integration, focusing on interoperability, sustainability, adaptability, stakeholder collaboration, and strong data governance. We propose a structured framework that puts these principles into action, outlining strategic routes for incorporating digital twin and Building Information Modeling (BIM) technologies into FoF, establishing public-private partnerships, enhancing education and workforce development, and setting up mechanisms for ongoing evaluation and enhancement. The potential of this integration to transform urban development is vast, providing a model for boosting operational efficiency, driving economic growth, and enhancing urban livability. Although challenges exist in realizing this vision, our research offers practical insights and strategies for cities and industries to effectively navigate the complexities of the digital era. This contribution enriches the growing field of urban science, advocating for a harmonious integration of industrial production with urban development in the Smart Cities framework. [ABSTRACT FROM AUTHOR]

The recent rise in the applications of advanced technologies in the sustainable design and construction of transportation infrastructure demands an appropriate medium for their integration and utilization. The relatively new concept of Civil Integrated Management (CIM) is such a medium; it enhances the development of digital twins for infrastructure and also embodies various practices and tools, including the collection, organization, and data-management techniques of digital data for transportation infrastructure projects. This paper presents a comprehensive analysis of advanced CIM tools and technologies and categorizes its findings into the following research topics: application of advanced surveying methods (Advanced Surveying); geospatial analysis tools for project planning (Geospatial Analysis); multidimensional virtual design models (nD Modeling); Integrated Geospatial and Building Information Modeling (GeoBIM); and transportation infrastructure maintenance and rehabilitation planning (Asset Management). Despite challenges such as modeling complexity, technology investment, and data security, the integration of GIS, BIM, and artificial intelligence within asset-management systems hold the potential to improve infrastructure's structural integrity and long-term performance through automated monitoring, analysis, and predictive maintenance during its lifetime. [ABSTRACT FROM AUTHOR]

In response to the critical need for enhanced resource management in the construction industry, this research develops an innovative, integrated methodology that synergistically combines Agent-Based Modeling (ABM), Building Information Modeling (BIM), and Bluetooth Low Energy (BLE) technologies. Central to our approach is a sophisticated technological framework that incorporates a Client Early Warning System (CEWS) and a Decision Support System (DSS). These systems facilitate real-time monitoring and management of construction resources, ensuring operational efficiency and optimal resource utilization. Our methodology was empirically validated through a comprehensive case study at Helwan University's College of Engineering. The results demonstrated a significant enhancement in operational efficiency, particularly in resource allocation and progress tracking. Key practical outcomes include the development of a CEWS master dashboard that provides in-depth, real-time insights into project metrics. This dashboard was crucial for managing compliance with health protocols during the COVID-19 pandemic, showcasing the framework's adaptability to critical health standards. Further, the integration of indoor tracking technology revolutionized attendance tracking by replacing outdated manual methods with automated processes. This capability not only underscores the practical applicability of our research but also establishes a new benchmark for future technological advancements in construction project management. Our study sets the stage for subsequent innovations, paving the way for a more connected, efficient, and data-driven approach in the construction industry. [ABSTRACT FROM AUTHOR]

The global demand for energy is significantly impacted by the consumption patterns within the building sector. As such, the importance of energy simulation and prediction is growing exponentially. This research leverages Building Information Modelling (BIM) methodologies, creating a synergy between traditional software methods and algorithm-driven approaches for comprehensive energy analysis. The study also proposes a method for monitoring select energy management factors, a step that could potentially pave the way for the integration of digital twins in energy management systems. The research is grounded in a case study of a newly constructed educational building in New South Wales, Australia. The digital physical model of the building was created using Autodesk Revit, a conventional software for BIM methodology. EnergyPlus, facilitated by OpenStudio, was employed for the traditional software-based energy analysis. The energy analysis output was then used to develop preliminary algorithm models using regression strategies in Python. In this regression analysis, the temperature and relative humidity of each energy unit were used as independent variables, with their energy consumption being the dependent variable. The sigmoid algorithm model, known for its accuracy and interpretability, was employed for advanced energy simulation. This was combined with sensor data for real-time energy prediction. A basic digital twin (DT) example was created to simulate the dynamic control of air conditioning and lighting, showcasing the adaptability and effectiveness of the system. The study also explores the potential of machine learning, specifically reinforcement learning, in optimizing energy management in response to environmental changes and usage conditions. Despite the current limitations, the study identifies potential future research directions. These include enhancing model accuracy and developing complex algorithms to boost energy efficiency and reduce costs. [ABSTRACT FROM AUTHOR]

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This paper is part of an ongoing research study on developing a methodology for the low-cost creation of the Digital Twin of an urban neighborhood for sustainable, transparent, and participatory urban management to enable low-and middle-income economies to meet the UN Sustainable Development Agenda 2030 successfully and timely, in particular SDGs 1, 7, 9, 10, 11, and 12. The methodology includes: (1) the creation of a geospatial data infrastructure by merging Building Information Models (BIMs) and 3D cadastral data that may support a number of applications (i.e., visualization of 3D volumetric legal entities), and (2) the use of Artificial Intelligence (AI) platforms, Machine Learning (ML), and sensors that are interconnected with devices located in the various property units to test and predict future scenarios and support energy efficiency applications. Two modular platforms are created: (1) to interact with the AI sensors for building tracking and management purposes (i.e., alarms, security cameras, control panels, etc.) and (2) to analyze the energy consumption data such as future predictions, anomaly detection, and scenario making. A case study is made for an urban neighborhood in Athens. It includes a dynamic weather simulation and visualization of different seasons and times of day in combination with internal energy consumption. [ABSTRACT FROM AUTHOR]

Defined digital Facilities' Management (FM) systems will contribute to the realisation of the United Nations' Sustainable Development Goal (SDG) 11. Of the available digital FM systems, Building Information Modelling (BIM) for FM, herein referred to as BIM-FM, is the least developed. Where BIM-FM varies from existing digital FM tools is its advanced 3D visualisation capabilities. A semi-structured literature review is undertaken to assess the current implementation of BIM-FM and identify opportunities to engender its increased adoption. This paper is part of an ongoing piece of research aimed at defining a standard methodology for the application of BIM to historically significant structures, otherwise known as Historic BIM (HBIM). Two existing approaches to BIM-FM, current and developing, are outlined. The potential value BIM-FM can provide according to the literature is discussed but there exists minimal practical evidence to justify these claims. Barriers to its adoption are discussed, with a key underlying barrier found to be a lack of defined user requirements. Consequently, functional, modelling and information requirements established within the literature are identified, and existing attempts at realising the requirements are discussed. Six information categories and two functional requirements are identified. It is theorised that the tendency to utilise simplified geometric models for FM is primarily due to software and practical limitations as opposed to actual end user needs, and it is suggested that this should be investigated further in future work. Attempts at realising BIM-FM user requirements using other advanced technologies, primarily Digital Twins, are investigated and found to be an area of increasing commonality. A new conception of BIM-FM is proposed. [ABSTRACT FROM AUTHOR]

This research paper explores the integration of novel technologies in hospital emergency evacuations, particularly in Operating Rooms (ORs) and Emergency Departments (EDs). It examines the application of advanced tools like simulation modeling, Building Information Modeling (BIM), Digital Twin technology, sensor data, and Artificial Intelligence (AI) to improve evacuation strategies in the building. The study extends to in-depth case studies for assessing the practicality of existing protocols, while also highlighting the critical importance of staff training and preparedness. Additionally, it addresses the ethical and psychological impacts of emergencies on patients and healthcare staff, underscoring the need for technology to be complemented with human-centered care. The paper concludes by emphasizing the ongoing necessity for innovative research in enhancing safety and operational resilience in healthcare emergency management. [ABSTRACT FROM AUTHOR]

Concert halls have led to increasingly complex spaces that cannot be thought of as static 'containers' anymore. This complexity makes them viable to be launched towards industry 4.0 and to be considered a function of the activities that they can provide during their life cycle. They are characterized by dynamic objects that contain sophisticated sub-systems and add to the capability to influence both environmental variables and user behavior. This article explains an adaptive concert hall at an early stage, in which a network of sensors that gather real-time data on environmental factors such as temperature, air humidity and air velocity are considered, focusing on their direct and indirect intercorrelations with the acoustic quantities to optimize the room acoustic response. The proposed methodology is controlled by a digital twin (DT) based on building information modeling (BIM), integrated with sensors, actuators, and acoustic measurements and algorithms. By analyzing the data, algorithms identify patterns, and an autonomous fine-tune setting is achieved, including the novelty for which a natural variable acoustic field becomes possible during a musical execution without the use of any electroacoustic system support. The hall becomes a natural active instrument to be included in the composer's score. A case study is presented. [ABSTRACT FROM AUTHOR]

In the dynamic realm of digital twin modeling, where advancements are swiftly unfolding, users now possess the unprecedented ability to capture and generate geospatial data in real time. This article delves into a critical exploration of this landscape by presenting a meticulously devised workflow tailored for the creation of Level of Detail 3 (LOD3) models. Our research methodology capitalizes on the integration of Apple LiDAR technology alongside photogrammetric point clouds acquired from Unmanned Aerial Vehicles (UAVs). The proposed process unfolds with the transformation of point cloud data into Industry Foundation Classes (IFC) models, which are subsequently refined into LOD3 Geographic Information System (GIS) models leveraging the Feature Manipulation Engine (FME) workbench 2022.1.2. This orchestrated synergy among Apple LiDAR, UAV-derived photogrammetric point clouds, and the transformative capabilities of the FME culminates in the development of precise LOD3 GIS models. Our proposed workflow revolutionizes this landscape by integrating multi-source point clouds, imbuing them with accurate semantics derived from IFC models, and culminating in the creation of valid CityGML LOD3 buildings through sophisticated 3D geometric operations. The implications of this technical innovation are profound. Firstly, it elevates the capacity to produce intricate infrastructure models, unlocking new vistas for modeling digital twins. Secondly, it extends the horizons of GIS applications by seamlessly integrating enriched Building Information Modeling (BIM) components, thereby enhancing decision-making processes and facilitating more comprehensive spatial analyses. [ABSTRACT FROM AUTHOR]

The integration of the Internet of Things (IoT) and Building Information Modeling (BIM) is progressing. The use of microcontrollers and sensors in buildings is described as a level 3B maturity in the use of BIM. Design companies, contractors and building operators can use IoT solutions to monitor, analyze or manage processes. As a rule, solutions based on original Arduino boards are quite an expensive investment. The aim of this research was to find a low-cost IoT solution for monitoring, analysis and management, and integrate it with a BIM model. In the present study, an inexpensive NodeMCU microcontroller and a temperature and pressure sensor were used to study the thermal comfort of users in a single-family home. During the summer season, analysis of the monitored temperature can contribute to installation (HVAC) or retrofit work (for energy efficiency). The article presents a low-cost solution for studying the thermal comfort of users using a digital twin built-in BIM. Data obtained from sensors can support both the design and management processes. The main contribution of the article enables the design, construction and use of low-cost circuits (15.57 USD) even in small developments (single-family houses, semi-detached houses, terraced houses, atrium buildings). Combining IoT sensor telemetry with BIM (maturity level 3C) is a challenge that organizations will face in the near future. [ABSTRACT FROM AUTHOR]

As digital transformation accelerates in the construction industry, combining data from Building Information Modelling (BIM) and 3D Geographic Information Systems (3DGIS) has become critical for enhanced decision-making across sectors including construction planning, supply chain management, health and safety and sustainable waste disposal. In combination, BIM and GIS underpin a location framework for Digital Twins across these applications. While traditionally relational databases have been used to integrate the data into one system, they face increasing limitations in handling the massive, complex BIM and 3DGIS data. This research investigates the potential of NoSQL databases as an alternative solution. Focusing on MongoDB, the study conducts a systematic performance comparison with the mature relational database, PostgreSQL. BIM and 3DGIS datasets from a live infrastructure construction project are utilised in three experiments assessing direct query, API-based retrieval, and 3D visualisation. The results provide valuable insights into MongoDB's strengths in managing large spatial data via flexible schemas. However, limitations surface as data complexity and volume increases. Overall, this study concludes that NoSQL databases do offer some advantages for optimising BIM-3DGIS integration for seamless, combined, use, but more work is needed to fully harness their capabilities. [ABSTRACT FROM AUTHOR]

Digital twins for medium span bridges – pilot project bridge Schwindegg – part 2: Asset Administration Shell The term ′digital twin′ is becoming increasingly popular in German‐speaking countries for the digital management and condition monitoring of bridges. Although standardised developments for the use of digital twins have already been initiated in industry and medicine, the first prototypes are currently being implemented in the construction industry. The digital images are typically operated in online environments that are proprietary to the project and have limited reusability. The article investigates the integration of scaling into Building Information Modelling models, which is reaching its limits due to the real‐time capability. It places existing definitions of the digital twin of the industry in the context of the construction industry. The implementation of the Isenbridge in Schwindegg as an Industry 4.0 Asset Administration Shell (AAS) is presented, building on Part 1 of this contribution. We show that an industrial, data‐driven digital twin can also be implemented technically and semantically for engineering structures. The article also presents the future challenges for evaluation and control mechanisms still to be developed for the structure. We also show a possible visualisation. The goal is to develop a syntax for the AAS' communication. [ABSTRACT FROM AUTHOR]

Rehearsal rooms play an important role in musicians' activities to obtain the best results during a performance in front of an audience. Numerous rehearsal rooms are located in complex buildings, such as opera houses and cultural centers, where new research outcomes have led to increasingly complex projects and construction phases. Furthermore, technical complexity has also increased due to the large quantity of used materials and the innovation level of the process. In this context, a new methodology becomes mandatory to control the indoor air quality and the acoustic quality in rehearsal rooms. This paper aims to offer a procedure for rehearsal rooms for large ensembles during the construction and life cycle phases to optimize the indoor environmental quality according to different types of ensembles and repertoires. In particular, rehearsal rooms with wood panel cladding are considered. The proposed methodology is controlled by a digital twin (DT) based on building information modeling (BIM), integrated with acoustic measurements, sensors and actuators aimed at implementing the database in real time. A case study is presented, in which the cladding system is described, the new methodology is applied, and the results are compared with the criteria suggested in the standard ISO 23591. [ABSTRACT FROM AUTHOR]

Purpose: Facilities management (FM) plays a key role in the performance of businesses to ensure the comfort of users and the sustainable use of natural resources over operation and maintenance. Nevertheless, reactive maintenance (RM) services are characterised by delays, waste and difficulties in prioritising services and identifying the root causes of failures; this is mostly caused by inefficient asset information and communication management. While linking building information modelling and the Internet of Things through a digital twin has demonstrated potential for improving FM practices, there is a lack of evidence regarding the process requirements involved in their implementation. This paper aims to address this challenge, as it is the first to statistically characterise RM services and processes to identify the most critical RM problems and scenarios for digital twin implementation. The statistical data analytics approach also constitutes a novel practical approach for a holistic analysis of RM occurrences. Design/methodology/approach: The research strategy was based on multiple case studies, which adopted university campuses as objects for investigation. A detailed literature review of work to date and documental analysis assisted in generating data on the FM sector and RM services, where qualitative and statistical analyses were applied to approximately 300,000 individual work requests. Findings: The work provides substantial evidence of a series of patterns across both cases that were not evidenced prior to this study: a concentration of requests within main campuses; a balanced distribution of requests per building, mechanical and electrical service categories; a predominance of low priority level services; a low rate of compliance in attending priority services; a cumulative impact on the overall picture of five problem subcategories (i.e. Building-Door, Mechanical-Plumbing, Electrical-Lighting, Mechanical-Heat/Cool/Ventilation and Electrical-Power); a predominance of problems in student accommodation facilities, circulations and offices; and a concentration of requests related to unlisted buildings. These new patterns form the basis for business cases where maintenance services and FM sectors can benefit from digital twins. It also provides a new methodological approach for assessing the impact of RM on businesses. Practical implications: The findings provide new insights for owners and FM staff in determining the criticality of RM services, justifying investments and planning the digital transformation of services for a smarter provision. Originality/value: This study represents a unique approach to FM and provides detailed evidence to identify novel RM patterns of critical service provision and activities within organisations for efficient digitalised data management over a building's lifecycle. [ABSTRACT FROM AUTHOR]

In the architecture, engineering, and construction industries, the integration of Building Information Modeling (BIM) has become instrumental in shaping the design and commissioning of smart buildings. At the center of this development is the pursuit of more intelligent, efficient, and sustainable built environments. The emergence of smart buildings equipped with advanced sensor networks and automation systems increasingly requires the implementation of Digital Twins (DT) for the direct coupling of BIM methods for integral building planning, commissioning, and operational monitoring. While simulation tools and methods exist in the design phase of developing advanced controls, their mapping to construction or post-construction models is less well developed. Through systematic, keyword-based literature research on publisher-independent databases, this review paper gives a comprehensive overview of the state of the research on BIM integration of building control systems with a primary focus on combined controls for daylight and artificial lighting systems. The review, supported by a bibliometric literature analysis, highlights major development fields in HVAC controls, failure detection, and fire-detection systems, while the integration of daylight and artificial lighting controls in Digital Twins is still at an early stage of development. In addition to already existing reviews in the context of BIM and Digital planning methods, this review particularly intends to build the necessary knowledge base to further motivate research activities to integrate simulation-based control methods in the BIM planning process and to further close the gap between planning, implementation, and commissioning. [ABSTRACT FROM AUTHOR]

The construction industry has been trying to enhance the level of digitalization and autonomy by adopting various communication and information technologies (ICT), e.g., augmented reality (AR), virtual reality (VR), robotics, drones, or building information modeling (BIM). However, improvement of the safety and productivity in their domains is still a struggle. One of the main reasons for failing to accelerate their digital transformation is ignoring the deep understanding of the concept of digital twin, its usage, and the potential benefits of digital twins in the construction industry. Therefore, this paper investigated the impacts and potentials of digital twins on the construction industry through a quantitative systematic review assisted by the text mining method. The study presented the potential usability of digital twins, leading and core technologies, and applications, revealing their benefits and potential for optimizing project planning, execution, and management process. Through this comprehensive literature review, this study elucidated the distinctive features, advantages, and immense potential that digital twins bring to the construction field. The findings highlight the transformative impact of digital twins, providing critical insights for their broader adoption and groundbreaking applications in the industry. By addressing the challenges of adopting this technology, the article provided valuable insights for advancing research and the broad implementation of digital twins in the sector. [ABSTRACT FROM AUTHOR]

The majority of Europe's building stock consists of facilities built before 2001, presenting a substantial opportunity for energy efficiency improvements during their operation and maintenance phase. Digitalizing these buildings with digital twin technology can significantly enhance their energy efficiency. Reviewing the applications and trends of digital twins in this context is beneficial to understand the current state of the art and the specific challenges encountered when applying this technology to older buildings. This study focuses on the application of digital twins in building operations and maintenance (O & M), emphasizing energy efficiency throughout the building lifetime. A systematic process to select 21 pertinent use-case studies was performed, complemented by an analysis of six enterprise-level digital twin solutions. This was followed by an overview of general characteristics, thematic classification, detailed individual study analyses, and a comparison of digital twin solutions with commercial tools. Five main applications of digital twins were identified and examined: component monitoring, anomaly detection, operational optimization, predictive maintenance and simulation of alternative scenarios. The paper highlights challenges like the reliance on Building Information Modeling (BIM) and the need for robust data acquisition systems. These limitations hinder the implementation of digital twins, in particular in existing buildings with no digital information available. It concludes with future research directions emphasizing the development of methods not solely reliant on BIM data, integration challenges, and potential enhancements through AI and machine learning applications. [ABSTRACT FROM AUTHOR]

At present, increased modes of transport have facilitated daily life. Building information modeling (BIM) integration has become a key strategy to foster efficiency, collaboration, and sustainability in the fields of buildings, transport, and facilities. Currently, there is a scarcity of comprehensive examinations of the performance of integrated BIM with transport facilities and applications to help identify potential prospects for sustainable development. Hence, this research paper attempts to scrutinize the integration of BIM, transportation, and facilities (T and Fs) by highlighting future directions and trends, revealing the existing status and hotspots of research in the field, and clarifying the developmental pulse of research as well as emerging areas in the future. A quantitative research technique is utilized in this study, using VOSviewer and CiteSpace software, and the Web of Science Core Collection (WoSCC) database. The study findings suggest that the hot keywords for the integration of BIM and T and Fs are predominantly concentrated on construction, framework, system, design, and management. In addition, over the previous 34 years (years 1989 to 2023), the applications of point cloud, digital twin, and life cycle assessment have been the current hot topics, and these emerging technologies can offer more innovative breakthroughs for the future. Furthermore, the integration of BIM and T and Fs represents an important trend that is essential for improving the efficiency, sustainability, and intelligence of buildings and infrastructure, from which the three domains can create synergies that contribute to the better planning, construction, and management of building and infrastructure projects. [ABSTRACT FROM AUTHOR]

The metaverse is seen as a future generation of the Internet in which the virtual and the real merge into a common world. Technologies such as IoT, cloud computing, artificial intelligence or the reality–virtuality continuum underpin the metaverse and condition its evolution. This paper presents a bibliometric study on the WoS database (from 1995 to 2022) to obtain a comprehensive and non-subjective understanding of the metaverse. The study identifies the main subject areas and sources, the leading countries and authors. It also analyzes the evolution over time and the core and future research themes. Extended reality, blockchain, artificial intelligence and sensors are identified as core themes, while building information modeling, digital twins and governance emerge as future themes. Based on the bibliometric study, a general layered metaverse architecture is proposed that streamlines open challenges in the metaverse to assist researchers and companies in introducing innovative and disruptive improvements. [ABSTRACT FROM AUTHOR]

The emergence of Digital Twin (DT) technology presents unique opportunities for society by facilitating real-time data transfer from the physical environment to its digital counterpart. Although progress has been made in various industry sectors such as aerospace, the Architecture, Engineering, Construction, and Operation (AECO) sector still requires further advancements, like the adoption of these technologies over traditional approaches. The use of these technologies should become standard practice rather than an advanced operation. This paper aims to address the existing gap by presenting a comprehensive framework that integrates technologies and concepts derived from purpose-driven case studies and research studies across different industries. The framework is designed to provide best practices for the AECO sector. Moreover, it aims to underscores the potential of DT for optimization through overseeing and digital management of the built environment across the entire life cycle of facilities, encompassing design, construction, operation, and maintenance. It is based on an extensive literature review and presents a holistic approach to outlining the roles of Building Information Modelling (BIM), Geographic Information Systems (GIS), Internet of Things (IoT), and other key enablers within the DT environment. These digital tools facilitating the simultaneous evaluation of associated benefits, such as resource savings and future prospects, like monitoring project sustainability objectives. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Complex demands in the field of cultural heritage preservation often require a multidisciplinary approach and substantial volumes of multimodal data integration and management. The conventional approach to tackling these issues revolves around using different H-BIM (historical building information model) solutions. This paper presents a prototype for a web platform that moves closer to the idea of a digital twin for physical cultural assets. Based on a light development framework, it is designed for online open access and features a versatile custom 3D viewer for intuitive interaction with the presented data. The concept requires a workflow similar to the video-game industry's 3D asset optimization to generate highly detailed 3D models and to facilitate the display of multilayered imaging data. The technological stack features a minimal MVC architecture framework and front-end stylesheets. It is designed to be independent of specific databases, enhancing portability for potential future open-source releases. Moreover, the platform employs WebGL libraries to create a dynamic 3D environment interaction. The capabilities of the web platform were tested in a case study regarding the documentation of an important 17th-century church in Romania. Further developments and current limitations of the platform are also discussed. [ABSTRACT FROM AUTHOR]

Digital twins aim to virtually replicate the static and dynamic building characteristics through real-time connectivity between virtual and physical counterparts. Despite its potential, research into digital twins for facility management (FM) in multipurpose spaces is at an early stage, especially to control and optimize the various uses and configuration layouts. One of the major barriers to the adoption of digital twin technology in multipurpose buildings is the lack of interoperability, primarily between building information modeling (BIM) and Internet of things (IoT) data sources. This paper presents a possible digital-twin architecture to enable digital-twin applications aiming to impact building performance, acting on the facility management of stagecraft and variable acoustic architectural elements to control the reverberation time in real time. The case study of Roberto De Silva Multipurpose Hall is presented, in which the indoor acoustic quality is controlled by the digital twin that returns the reverberation time output as a function of stage equipment layouts, variable acoustic elements and hall occupancy. [ABSTRACT FROM AUTHOR]

It is obvious that the primary document will always be the building itself, but within the field of conservation, restoration or maintenance it is necessary to have a large documentary archive where the interventions are recorded. The older the monument is, the greater the knowledge of the built element must be before any intervention and this requires a lot of time in prior research and which can develop prior studies, in addition to the economic cost that it entails. This is why with the advancement of technology and digital repositories, digital platforms can be created within Heritage Building Information Modeling (HBIM). This article reflects the experience of an eight-century-old monument, San Juan of Hospital of Valencia (Spain), in which a virtual twin has been made with software and specific web platforms in facility management such as Archibus©, EcoDomus©, Zutec© that allow the integration of information from BIM models and data acquired through sensors. With this work, although it is economically expensive and requires a lot of time for people specialized in the required programs, is improving the efficiency of facility management. and maintenance planning for large buildings and infrastructure. [ABSTRACT FROM AUTHOR]

The reprocessing, preservation, and maintenance of Italy's extensive historical architectural heritage, represent a relevant challenge for digitalization, considering that it is not only among the oldest in Europe but is also widespread across the country, encompassing both urban and rural areas. The care of such an aging-built environment needs a carefully planned approach that can take advantage of new technologies such as Historical/Heritage Building Information Modelling (H-BIM) and Digital Twin (DT). The final goal is to promote a long-term sustainable restoration, implying high qualitative standards. The topic of sustainability is often focused on new constructions, where it is of fundamental importance to save materials, energy, and land use, as well as decrease the carbon footprint. However, it is important to apply innovative digital management technologies to historical buildings in Italy, which are way more fragile if compared to modern ones. Cultural heritage is in general subject to specific challenges that need to be addressed, especially considering extreme events such as the earthquake that occurred in the L'Aquila Region in 2019, or in the area of Amatrice in 2016 affecting Marche and Umbria Regions. Digital technologies can be used to prevent or at least mitigate the effects of those kinds of catastrophic events, limiting damages and saving human lives, but also providing valuable information, and creating tools to be shared among stakeholders, to restore the physical and cultural value of a historical building, even in case of extreme events. [ABSTRACT FROM AUTHOR]

Non‐destructive testing in civil engineering is a fast‐emerging field. This includes not only new devices, sensors, and techniques for the inspection of materials, components, and structures contributing to building information modeling (BIM) but also efficient concepts for structural health monitoring in the frame of digital twins. The paper highlights some of these new developments and examples for applications covering the design of new construction materials, quality control during construction, contributions to predictive maintenance, and finally the rehabilitation and repair of structures. The new demands and techniques require new training concepts for the qualification of experts for the construction industry but also well‐structured courses for the academic education of students. Some new standards for training and education will be introduced. This paves the way for modern, efficient, and reliable applications of non‐destructive testing and structural health methods. [ABSTRACT FROM AUTHOR]

There has been a recent interest in the field of digital heritage to advance historic building information modeling (HBIM) towards digital twins (DT). This paper investigates the potential and limitations of HBIM use as DTs through a systematic mapping of literature (SML). The conclusions were applied in an incremental and low-code workflow to model historic buildings aiming at achieving a trade-off between a high degree of parametrization and a high degree of geometric accuracy. The proposed workflow is illustrated through a parametric script developed with visual programming in Grasshopper for Rhino 3D to model historic columns from profiles. VisualARQ for Rhino 3D is used to convert the script into a BIM object that uses profiles, automatically extracted from a point cloud acquired with 3D laser scanning, as an initial shape. This results in a simpler workflow to achieve more accurate HBIM models that could be leveraged in DT simulations. [ABSTRACT FROM AUTHOR]

The construction industry’s reliance on traditional methods and fragmented workflows results in significant information loss, inefficiencies, increased costs, and errors. This study addresses these issues by integrating comprehensive urban planning with building information modeling (BIM) to create a seamless information flow throughout the building lifecycle. We propose a holistic framework that synchronizes data from planning to demolition, incorporating national and municipal digital twins. An imperative literature review and analysis of international best practices were conducted to develop a conceptual framework aimed at improving data accuracy and interoperability. Our findings underscore the importance of adopting open standards such as Industry Foundation Classes (IFC) and CityGML for effective information exchange. By implementing an information model (IM)-based approach in urban planning and public sector permit processes, project timelines can be streamlined, and regulatory compliance enhanced. This study concludes that continuous, integrated information flow facilitates more efficient, cost-effective construction practices and improved decision-making. Furthermore, this research illustrates the potential of digital twin technology to revolutionize the construction industry by enabling real-time data integration and fostering stakeholder collaboration, ultimately offering a robust framework for practitioners, and significantly enhancing the efficiency and accuracy of construction processes.

Featured Application: Developed research may be applied to the digitization of the operation of industrial objects. The current industrial facility market necessitates the digitization of both production and infrastructure to ensure compatibility. This digitization is presently accomplished using Building Information Modeling and digital twin technologies, as well as their integrated usage, which enhances convergence and adds further value to facility assets. However, these technologies primarily focus on the physical components of industrial facilities, neglecting processes, requirements, and functions. To address these gaps, the inclusion of the Model-Based System Engineering approach, a proven benchmark in systems engineering, is essential. This inclusion is the main objective of this research. This article outlines methods and principles for integrating Model-Based System Engineering into the informational modeling of existing industrial facilities to address current market gaps. It offers practical steps for such integration and compares it to other methods, positioning Model-Based System Engineering as a pivotal tool for enhancing the value of industrial facility digital assets. The main findings include the proposal of BIM and MBSE integration, which aims to create a competitive advantage for industrial facilities by improving customer service and operational efficiency, requiring collaboration from various stakeholders. [ABSTRACT FROM AUTHOR]

Image-based techniques have become integral to the construction sector, aiding in project planning, progress monitoring, quality control, and documentation. In this paper, we address two key challenges that limit our ability to fully exploit the potential of images. The first is the "semantic gap" between low-level image features and high-level semantic descriptions. The second is the lack of principled integration between images and other digital systems used in construction, such as construction schedules and building information modeling (BIM). These challenges make it difficult to effectively incorporate images into digital twins of construction (DTC), a critical concept that addresses the construction industry's need for more efficient project management and decision-making. To address these challenges, we first propose an ontology-based construction image interpretation (CII) framework to formalize the interpretation and integration workflow. Then, the DiCon-SII ontology is developed to provide a formalized vocabulary for visual construction contents and features. DiCon-SII also acts as a bridge between images and other digital systems to help construct an image-involved DTC. To evaluate the practical application of DiCon-SII and CII in supporting construction management tasks and as a precursor to DTC, we conducted a case study involving drywall installation. Via this case study, we demonstrate how the proposed methods can be used to infer the operational stage of a construction process, estimate labor productivity, and retrieve specific images based on user queries. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Building Information Modeling (BIM) has catalyzed transformative shifts across various industries, which has sparked broader research interests in the BIM lifecycle. However, studies that specify the stated requirements for different technologies and methodologies from the perspective of the BIM lifecycle and analyze research hotspots and future research trends at each stage are scarce. Employing scientometric theories and methods, this study conducts an in-depth comparative analysis of BIM lifecycle stages. The analysis encompasses several aspects like annual research output and knowledge flows, in the aim of unveiling disparities in the technological requirements, defining research boundaries, and illuminating lifecycle research trends. Findings indicate an ongoing surge in research across all BIM lifecycle stages with technologies like digital twins and artificial intelligence becoming prevailing trends. The cooperative design of BIM components, virtual-real world coordination, interactions among buildings, individuals, and environments, as well as the in-depth integration of BIM with the multifaceted fields of urban management have emerged as focal points in the planning, construction, management, and maintenance of BIM, respectively. Future BIM lifecycle research will necessitate interdisciplinary collaboration, emphasizing technological integration, common data environment (CDE) information sharing, open-source BIM/historic building information modeling (HBIM) system, and impactful exploration in areas like urban construction and historical preservation. [ABSTRACT FROM AUTHOR]

With the advancement of state-of-the-art technologies, the semiconductor industry plays a key role as an essential component in the manufacture of various electronic products. Since the manufacturing of a semiconductor goes through very sophisticated and complex processes, efficient and accurate work and management are essential in the design, construction, and operation stages of the semiconductor fabrication (FAB) plant. Recently, the combined application of building information modeling (BIM) and augmented reality (AR) technology has gained increased attention in this semiconductor FAB industry as an advanced way to improve work efficiency and accuracy while eliminating other related problems, such as human errors. Despite the perceived benefits of combined use of BIM and AR, many technical problems still exist when integrating the target test model and the 3D virtual object model using BIM data and existing AR visualization technology, due to the unique characteristics of the FAB sites. To solve these problems, this study proposed an AR-based real-time BIM data compatibility verification method for future FAB digital twin implementation and demonstrated that it could be converted into a system and applied to actual FAB sites. As a result of the development and verification of this system, the proposed AR-based real-time BIM data compatibility verification system enables the accurate fitting of the AR model and actual object through AR tracking and anchoring technology considering the characteristics of FAB sites. After the fitting, the system was able to maintain compatibility, even when the camera moved and the marker moved away from the screen. By expanding the effective distance of compatibility between the AR model and the actual object, it was possible to increase the AR application range between the 3D virtual object model and the test target model and to improve the compatibility. [ABSTRACT FROM AUTHOR]

Confronted with the climate crisis, the world is making tremendous efforts in energy transition, such as expanding renewable energy that does not emit carbon. The importance of virtual power plant (VPP) operation technology has emerged to secure grid flexibility in response to the expanding renewable energy implemented due to these efforts. Accordingly, VPPs, which include photovoltaics, wind turbines, heating, ventilation, and air conditioning (HVAC), load, and EV, have been constructed. HVAC, one of the component resources, is a system that controls and regulates temperature, humidity, and airflow. Since it responds sensitively to the building's heat capacity and changes in the external environment, it requires continuous and stable control. In this paper, we used data-based modeling to implement the HVAC required for the optimal operation of VPP. Since accurately creating an equation-based HVAC model was difficult considering building information modeling and external environment variables, we used historical HVAC operation data to perform data-based modeling. The model was implemented using nonlinear regression and machine learning, such as a support vector machine and artificial neural network. Then, the data-based HVAC and the actual HVAC operation results were comparatively analyzed based on a case study, and the model's goodness-of-fit was evaluated based on performance metrics. Model performance indicators confirmed that the ANN-based HVAC model was most similar to the actual HVAC system. [ABSTRACT FROM AUTHOR]

Roads and highways are often managed by using Geographic Information Systems (GIS). However, these systems lack the level of detail that Building Information Modelling (BIM) can bring to an infrastructure management system. BMGIS integration allows the management of information from both infrastructure and environmental points of view. This provides an overview of the infrastructure, facilitating decision-making process throughout its complete life cycle. This article shows a semi-automated process to generate the hybrid BIM-GIS model of Madrid Calle30. The model together with an external database was uploaded to an intelligent management platform that allows visualising the available documentation, assisting management, and bringing the ring-road closer to a digital twin of the infrastructure. [ABSTRACT FROM AUTHOR]

With the development and popularization of the Internet of Things, big data, cloud computing, and other technologies, Digital twin technology (DTT) is increasingly applied to building operation and maintenance (O&M). However, most of the research focuses on building energy consumption, safety, and other management, and relatively little research on the monitoring of building terminal energy using information. The information is closely related to occupants' behavior, such as air conditioning, lighting, shading, window status information, as well as personnel number and location, and it has a great impact on building energy consumption. Due to different occupants' behaviors, the level of building energy consumption varies several times or even more. Take an office building as an example. Based on digital twin technology, the framework of building energy using intelligent monitoring is constructed. It mainly includes four parts, namely building physical space, virtual twin space, predictive control simulation engine, and twin big data. For each part, functions are realized through building Information Modelling (BIM), smart sensors, and Internet of Things (IoT) technologies. Based on the standard framework and every function realization method, the DTT can used for building O&M effectually. The application of building an intelligent control system based on the occupants' characteristics is simulated and analyzed in Designbuilder software 6.1.2. The results show that the digital technology application in building intelligent control systems can realize maximum energy saving for 30%. However, the DTT in building O&M is not widely used now. There is a lot of research to be completed in the future. [ABSTRACT FROM AUTHOR]