Building Information Modeling Research Articles

Transforming fire protection: AI's evolving role in proactive and reactive applications

Abstract. This paper comprehensively reviews the applications of artificial intelligence (AI) in the field of fire protection. It traces the historical development of AI, from its origins in the 1930s and 1940s to its current state, focusing on major milestones and algorithms that have shaped the field. The paper discusses the evolution of AI, particularly in terms of machine learning, deep learning, and the emergence of various models such as deep neural networks (DNNs), transformer models, and graph neural networks (GNNs). The application of AI in fire protection is explored in two primary categories: proactive and reactive applications. Proactive applications encompass AI's role in decision-making, construction, and operation, including the use of machine learning for environmental analysis, building information modelling (BIM) for design optimization, 3D printing and intelligent robots in construction, and intelligent fire facility management. Reactive applications focus on early fire detection and monitoring, especially in forests, utilizing terrestrial, aerial, and satellite systems equipped with advanced sensors and deep learning techniques. This paper highlights the significant contributions of AI in mitigating fire risks, improving fire detection and response, and enhancing the safety and efficiency of fire protection systems.

Developing a Workflow for Transforming BIM Models into Immersive Virtual Reality Experiences

Abstract. The integration of Extended Reality (XR) and Building Information Modelling (BIM) has emerged as a promising approach for enhancing interaction with spatial data in the built environment. While the potential of BIM for advanced visualization has been recognized, there remains a need for standardized workflows that facilitate the transformation of BIM models into immersive virtual reality (VR) experiences. This research contributes to the ongoing development of BIM-VR integration by presenting a workflow that leverages Revit, Twinmotion, and Datasmith to create visually rich and interactive VR environments. The established process focuses on enhancing textures, incorporating dynamic lighting and weather simulations, and populating the virtual space with realistic elements. The workflow also addresses the integration of interactable objects to elevate user engagement and the use of cutting-edge VR headsets for an immersive experience. By providing a structured approach to bridging complex BIM data with VR, this research aims to support architects, engineers, construction professionals, and clients in design collaboration, project review, and decision-making across the building lifecycle. The workflow's potential for facilities management and training applications is also explored. Through a case study, the research demonstrates the workflow's effectiveness in facilitating a deeper understanding of architectural spaces before construction, highlighting its potential for improving efficiency and reducing rework. The paper also discusses the challenges and opportunities associated with integrating BIM with GIS and sensor data to create comprehensive digital twins. This research contributes to the growing body of knowledge on BIM-VR integration and underscores the importance of continued development in this field to enhance the design, communication, and experience of the built environment.

BG-LoA: A Benchmarking Framework for BIM/GIS Data Integration Based on Meta-Modelling Theory

Abstract. There are various studies on the integration of building information modelling (BIM) and geographic information system (GIS) that convert BIM data into GIS data. These studies used different technologies, data standards, data models, and data formats such as RDF (Resource Description Framework), graph, CityGML, and Shapefile to address the data incompatibility problem between BIM and GIS. This makes it difficult to compare these studies for the purpose of assessing research innovation, and sometimes, improper comparisons were carried out between studies. To solve this problem, this study adopted the metamodeling theory used in model-driven software engineering (MDSE) and extended its 4-layer framework of level of abstraction. The new benchmarking framework, referred to as level of abstraction for BIM/GIS data integration (BG-LoA), has 5 levels, including meta metamodel (M3), metamodel (M2), model (M1), reality (data) (M0), and reality (real world) (M00). The common types of IFC (Industry Foundation Classes) conversion were analysed using the new framework, including IFC-to-CityGML, IFC-to-CityJSON, IFC-to-Shapefile, IFC-to-GML, IFC-to-3DTiles, IFC-to-RDF, IFC-to-IfcGraph, and IFC-to-UML. The result shows that the new framework can show the difference between those conversion types, which makes it easier for future studies to benchmark their work and assess level of contribution to the body of knowledge.

OS DESAFIOS DA IMPLANTAÇÃO DA METODOLOGIA BIM EM ESCRITÓRIOS DE ARQUITETURA NA CIDADE DE VITÓRIA DA CONQUISTA – BA

Building Information Modeling (BIM) can be defined as a methodology that uses 3D models and their detailed data on all elements involved in a civil construction project. As society is a constantly evolving organism, the Construction Industry has faced the need to adapt in order to deliver better productivity results, thereby meeting increasingly meticulous demands more effectively. Scientific research has shown that the use of BIM can reduce project completion times in infrastructure by up to half. Given this, why is the number of architecture and urban planning firms in Vitória da Conquista – BA, that use this methodology still so minimal? This article, through bibliographic research as well as opinion surveys with architects and urban planners from the city of Vitória da Conquista, aims to demonstrate the challenges of implementing Building Information Modeling (BIM) methodology in offices in Vitória da Conquista – BA. Thus, the points discussed in this work will provide a reflection on this question, the conclusion of which will depend on the awareness and experience of each participating architect, as well as the robustness of the understandings used to support the content in the following sections.

Expanding Understandings of Curatorial Practice Through Virtual Exhibition Building

This article reflects on the translation of gallery space into a virtually immersive experience in an era of remote access. Curators and scholars such as Mary Nooter Roberts, Susan Vogel, Carol Duncan, Tony Bennet, Stephen Greenblatt, Judith Mastai, and Barbara Kirshenblatt-Gimblett have discussed the myriad of ways in which the experience of culturally significant objects and sites in person has been critical to the study of art and its history. Focusing on theories of curation and display, I utilize practice-based examples from six virtual reality (VR) exhibitions produced in three different institutional contexts: the International Journal of Digital Art History’s online gallery, the European Cultural Center’s Performance Art program, and the Digital Humanities program at the University of California, Los Angeles. By documenting and analyzing the extended reality (XR) methods employed and the methodological approaches to the digital curatorial work, I address some of the challenges and opportunities of presenting objects in virtual space, offering comparisons to those faced when building physical exhibitions. I also consider how digital modalities provide a distinctly different paradigm for epistemologies of art and culture that offer greater contextualized understandings and can reshape exhibition documentation and the teaching of curatorial practice and museum studies.

Urban Wastewater Management Using BIM Method

Building Information Modeling (BIM) is a method that emphasizes object-based data management, communication, and collaboration among all project participants throughout the entire lifecycle of a system. It is becoming an international standard for large-scale construction and infrastructure projects. Although BIM is gaining traction in the wastewater industry, the literature on its application in this field is still limited. This research, through expert interviews and literature review, explores the extent to which BIM has been introduced in the sewage industry and the associated opportunities and challenges. Initial projects in wastewater management using BIM include the construction and development of sewage treatment plants and special structures. Planning offices are leading the way in adopting BIM, supported by catalogs of industry-specific objects, clear definitions of responsibilities, and the potential for enhanced operation of sewage systems. Some users have already recognized the benefits of BIM and adjusted their processes accordingly. BIM’s object-oriented modeling improves the visualization of construction projects and processes, offering significant advantages in model-based plan derivation and mass determination. It also focuses on the collection, exchange, and storage of relevant data, which can benefit the entire wastewater industry. The research confirms that BIM adds value to wastewater management, especially since infrastructure is often difficult to access post-construction and knowledge about the systems is typically limited to those involved in the construction phase. However, to fully and effectively utilize BIM, further improvements are necessary. This requires intensive collaboration among project participants, software producers, and customers. The integration of BIM in wastewater management holds promise, but its successful implementation depends on overcoming current challenges and enhancing the method through collective effort. DOI: https://doi.org/10.52783/pst.928

BIM and IFC Data Readiness for AI Integration in the Construction Industry: A Review Approach

Building Information Modelling (BIM) has been increasingly integrated with Artificial Intelligence (AI) solutions to automate building construction processes. However, the methods for effectively transforming data from BIM formats, such as Industry Foundation Classes (IFC), into formats suitable for AI applications still need to be explored. This paper conducts a Systematic Literature Review (SLR) following the PRISMA guidelines to analyse current data preparation approaches in BIM applications. The goal is to identify the most suitable methods for AI integration by reviewing current data preparation practices in BIM applications. The review included a total of 93 articles from SCOPUS and WoS. The results include eight common data types, two data management frameworks, and four primary data conversion methods. Further analysis identified three barriers: first, the IFC format’s lack of support for time-series data; second, limitations in extracting geometric information from BIM models; and third, the absence of established toolchains to convert IFC files into usable formats. Based on the evidence, the data readiness is at an intermediate level. This research may serve as a guideline for future studies to address the limitations in data preparation within BIM for AI integration.

BIM-Supported Knowledge Collaboration: A Case Study of a Highway Project in China

Collaboration is challenging in highway building projects since there are always a number of stakeholders involved, each with different responsibilities, backgrounds, objectives, and competing interests. The basis for addressing collaboration problems in building projects is knowledge. Knowledge management (KM) can benefit greatly from the distinctive characteristics of BIM (building information modeling). Therefore, the purpose of this study is to investigate knowledge collaboration in highway construction projects that is enabled by BIM. It first explores the motivations behind and difficulties with using BIM for knowledge-based collaboration. Next, it looks for possible ways to overcome those difficulties. It employs a large highway project as a study case in China. It uses in-depth interviews with a range of contractors working on this project to comprehend the difficulties they face in working together and investigate ways that BIM-supported KM can help stakeholders collaborate more effectively. Ultimately, it creates a conceptual model for knowledge-driven collaborative management within the BIM environment, offering both a theoretical framework and useful direction for knowledge-based collaboration amongst various stakeholders. The study explores the advantages of BIM characteristics in knowledge collaboration, which provides empirical evidence for the transformation from traditional IT-based knowledge collaboration to BIM-based knowledge collaboration in large and complex highway projects.

Institutional shaping of CDE implementation in BIM-enabled AEC projects

The common data environment (CDE) for information sharing is one of the fundamental requirements for effective workflow management to harness the potential of building information modeling (BIM). While studies are replete on BIM from a technology adoption perspective, notably lacking in the literature is the understanding of the influence of institutions and their pressures on CDE adoption as an information management platform. This study aims to address this gap. Using the action research approach, a flagship university construction project in India was studied to understand the interplay of institutions and CDE adoption. Institutional theory was used as a theoretical lens to illuminate and analyze the implementation issues of CDE. The findings show that CDE implementation undergoes a series of transformations due to institutional pressures. The responses to institutional pressures are conformance, coupling and decoupling, and mutations. Insights of this study guide practitioners to be aware of the processes through which institutional pressures contextualize and transform the intended change. Accordingly, findings can help managers and public sector agents on aspects related to nudging and shaping the implementation of change through action strategies and tactics. The study extends the BIM adoption/localization literature by highlighting that institutional pressures modify the objectives of CDE. It theorizes the processes through which institutional pressures contextualize and transform a change agenda.

A study on the digital restoration of an ancient city based on historic building information modeling of wooden architectural heritage: focusing on Suwon Hwaseong

This study describes the process of digitally reconstructing the ancient Korean city of Suwon Hwaseong in 3D utilizing Historic Building Information Modeling (HBIM) resources to accurately represent its wooden architectural heritage. Previous 3D reconstructions of cultural heritage have often prioritized appearance or remained partially disassembled. However, our reconstruction method offers a comprehensive representation of the appearance and the internal structure of wooden architectural heritage, which can be suitable for restoration maintenance. To ensure accuracy in digital restoration, we collected and utilized administrative records and historical materials, including the geography, fortress walls, folk houses, and Haenggung (the temporary palace of the Joseon Dynasty)—drawing from the archive of the Korean Cultural Heritage Service’s management records and the 1796 manuscript “Uigwe: Royal Protocols of the Hwaseong Fortress” which documents the construction of the ancient city of Suwon Hwaseong. Extensive architectural records were used to generate HBIM data, which digitized historical records, documents, and drawings to accurately represent the complex layout of the wooden architectural heritage. For the folk houses that lacked design records and the fortress walls that retained their original shape, we performed a digital restoration-based façade modeling. These elements of the ancient city of Suwon Hwaseong were assembled into a 3D model using Unreal Engine (version 5.1.1) to digitally reconstruct the city and enhance its visual representation. The digital restoration content, which utilizes visual effects and precise rendering from a game engine, can be used for the restoration, repair, and maintenance of both appearance and internal structures.

Integrating Surface-related Indicators of Coverage, Distance and Distribution for Quantifying Scan-to-BIM Confidence Level

Abstract. Scan-to-BIM is a widely-used approach to generate Building Information Modelling and by extension Digital Twin models in the architecture, engineering, and construction sector. The resulting models need to be as accurate as possible to ensure subsequent activities that make use of them can do so effectively. Quality assessment of point clouds and occlusion assessment of BIM outputted from Scan-to-BIM has been investigated. However, Scan-to-BIM systems currently do not provide proper metrics as to the confidence the user can have in the quality, in particular geometric quality of the outputted model. This paper addresses this gap by introducing a confidence index, for analysing the reliability of the generated 3D models and thereby quantifying the confidence the user can have in them. Index of confidence is itself derived from three more specific indices: index of coverage estimates the portion of the surface of the modelled element that is explained by the input point cloud. Index of distribution estimates how well the points explaining the modelled surfaces are distributed around the overall object’s surface. Index of distance defines the closeness of the generated element models to the input point cloud. The proposed indices are assessed using three real examples, demonstrating their adequacy.

Visionary constructs: revolutionizing students internships through BIM and extended reality synergy

ABSTRACT This study investigates the integration of Building Information Modeling (BIM) and Extended Reality (XR) technologies in construction education, focusing on their application in internship programs. Traditional internships often face limitations such as restricted exposure to complex scenarios and geographical constraints. To address these challenges, this research examines how BIM-XR technologies can bridge the gap between theoretical knowledge and practical application in the Architecture, Engineering, and Construction (AEC) disciplines. A mixed-methods approach was employed, combining qualitative data from interviews with students, educators, and industry professionals alongside quantitative survey data. This comprehensive methodology enabled an in-depth assessment of BIM-XR's impact on student learning outcomes and operational efficiency. The findings revealed that BIM-XR integration significantly enhances educational experiences by providing immersive simulations that help students visualize complex construction processes. This leads to better preparedness for real-world challenges, increased engagement, and more effective internships. Additionally, BIM-XR offers practical benefits for industry practices, such as improved project planning, real-time decision-making, and enhanced stakeholder collaboration. However, the study also highlights challenges, including the steep learning curve, limited access to necessary technologies, and high implementation costs. These limitations point to the need for comprehensive training programs, affordable technology options, and institutional support to ensure broader adoption. Looking ahead, the study suggests that further integration of BIM-XR with emerging technologies like Artificial Intelligence (AI), Machine Learning (ML), and the Internet of Things (IoT) could further enhance educational outcomes and industry practices.

Zone-based many-objective building decarbonization considering outdoor temperature and occupation uncertainty

Operational building decarbonization is challenging due to complex weather conditions and occupation uncertainty. This paper introduces a precise optimization framework integrating the building information modelling technique and intelligent algorithms to dynamically predict multi-scenario building carbon emissions and optimize the building emissions performance considering building zones and weather conditions. Firstly, the on-site data and building information modeling-supported building emissions simulation data are collected for model training. Secondly, using intelligent algorithms, zone-based hourly carbon emissions and multi-scenario carbon emissions prediction are conducted simultaneously. Thirdly, the optimal decarbonization strategies are conducted using intelligent algorithms under various weather conditions. This framework has been verified for decarbonization in a high-rise operational building. The results reveal that: (1) The carbon emissions prediction is highly consistent with the ground truth after considering the sub-zone correlations; the R2 for the west, south, and east zones are 0.900, 0.900, and 0.942, respectively; (2) The surrogate models can accurately predict carbon emissions and thermal comforts with all R2 are higher than 0.912. The optimization rate of the building reaches 59.2 % while the outdoor temperature is above 35 °C. (3) In the many-objective optimization model, considering occupation uncertainty makes the strategy close to the actual situation, reaching the decarbonization by 6815.23 kg compared to the empirical operation for the cooling period. This work provides a new path for operational building precise management and control-oriented optimization decarbonization.

Building material reuse: An optimization framework for sourcing new and reclaimed building materials

The process of sourcing Reclaimed Construction Materials (RCMs) is predominantly manual and hindered by the limited digital presence of RCMs. However, the advancing technological landscape provides an opportunity to create a modular framework that can assess the value proposition of New Construction Materials (NCMs) and RCMs for a project before acquiring them. A field study in the Kitchener/Waterloo region inspired the development of a framework that has three underlying systems encompassing digital tools for data collection and analysis: (1) The Real Environment uses 3D scanners and a spreadsheet software, (2) The Model Environment uses Building Information Modeling (BIM) software and a Life Cycle Assessment (LCA) tool, and (3) The Core Engine uses an optimization program. Real-world data collected from RCM stores (The Habitat for Humanity) and NCM stores (The Home Depot) are used for a realistic demonstration of the framework. By practically applying the framework to source window and door components for a modeled multi-residential building design, an integrated selection of 35% RCMs and 65% NCMs was proposed for the building design. Furthermore, sensitivity analysis is also performed for validation. The framework may disrupt the ongoing building design practices that deem material reuse problematic by enabling flexible sourcing of used and new building materials. A modular and iterative framework for facilitating reuse is thus contributed.

Optimizing Energy Efficiency with a Cloud-Based Model Predictive Control: A Case Study of a Multi-Family Building

The Energy Performance of Buildings Directive (EPBD) has set a target to achieve carbon-neutral building stock and generate 80% of its electricity from renewable sources by 2050. While Model Predictive Control (MPC) can contribute significantly to energy flexibility in buildings, its remote implementation remains relatively unexplored, especially in the residential sector. The purpose of this research is to demonstrate the reliability, robustness, and computational efficiency of a cloud-based application of an MPC called Smart Energy Management (SEM) on a multi-family residential building. The SEM was tested on a virtual building model in TRNSYS using an open-source distributed event streaming platform for data exchange and synchronization. Simplified models for thermal behavior prediction, including an R3C3 model of the building, were developed in C++. The SEM was evaluated in eight scenarios with varying weather conditions, optimization criteria, and runtime periods. The results demonstrate that the SEM maintains stability and robustness over a 2-week period with a 15-minute planning resolution while ensuring thermal comfort. The C++ implementation of the optimization algorithm enables SEM deployment on low-spec servers, supporting cost-effective applications in real buildings with minimal intervention.

Semantic Enrichment of Non-Graphical Data of a BIM Model of a Public Building from the Perspective of the Facility Manager

Building information modeling (BIM) is undeniably the most important trend in the digitization of the construction sector in recent years. BIM models currently being built are extremely geometrically rich, that is, they are modeled at a high level of detail in terms of geometry. Thanks to object-oriented programming paradigms, BIM models include high-level relationships to ensure interactions between objects, rapid view generation, and documentation. However, these models are not always equally rich in non-graphical data. This is true for parameters at the library object level, with which building object models are saturated, but also at the project, site, building, or floor levels according to the structure of the interoperable industry foundation classes (IFC) format. The current state of knowledge also lacks a clear methodology for inputting such data. For this reason, experimental work was undertaken on semantic enrichment in non-graphical data of a public building (a public kindergarten, Secemin, Poland), which has its BIM model at a high level of geometric detail but is poor in non-graphical data. As a result of the research and development work, all levels of the IFC structure were saturated with non-graphical data and validated, and the possibilities of their use were shown from the perspective of the facility manager. Documentation from the manager was used to achieve this goal, and selected analyses and simulations were performed on the enriched model. This article contributes to the discussion on semantic enrichment from CAD3D to BIM by presenting a detailed process for entering non-graphical data into a BIM model. The presented data entry method can be used by both modelers and facility managers. Thus, this paper fills an important research gap related to semantic enrichment in non-graphical data at different levels of the IFC structure.

Adoption challenges of building information modelling (BIM) and off-site construction (OSC) in healthcare construction: are they fellow sufferers?

PurposeOff-Site Construction (OSC) has received much government and public attention during and after COVID. Building Information Modelling (BIM) is an initiative discussed widely to promote OSC implementation. Although many policy promotions have been published, there are many challenges to implementing BIM and OSC in real life and questions of whether they really offer value to healthcare design professionals. This research aims to investigate BIM and OSC to understand their commonalities and differences of challenges by collecting empirical evidence from China’s healthcare construction.Design/methodology/approachThis exploratory research adopted a mixed method with a questionnaire survey and interviews. A total of 261 questionnaires were received (with 183 valid), followed by 31 semi-structured interviews.FindingsThis research reveals that although both OSC and BIM face similar adoption challenges and suspicious attitudes in real-life projects, their challenges’ connotations and reasons are different. OSC faces scepticism for its customisation costs and technical constraints, while BIM is seen as limited in utility and complex to integrate. Highlighting these as socio-technical challenges, the research advocates for an integrated framework to effectively implement OSC and BIM, addressing both technical and collaborative needs in healthcare construction.Originality/valueThis research examines OSC and BIM within the context of healthcare construction, a focus that is relatively underexplored. The research provides a juxtaposition of the perceived and practical challenges of adopting these technologies, revealing a gap between the industry’s expectations and the current capabilities of OSC and BIM, thereby contributing to the development of modern methods of design in healthcare.

Automatic Planning Method of Construction Schedule under Multi-Dimensional Spatial Resource Constraints

To enhance the application of building information modeling (BIM) in schedule management for engineering projects, improve spatial planning capabilities, and minimize subjective factors in schedule preparation, this paper presents a framework and method for automatic construction schedule planning based on BIM and data-driven approaches under multi-dimensional spatial resource constraints. The method includes data acquisition, construction process reasoning, time parameter calculation, and schedule generation and scheduling. Initially, the construction data from the BIM model and manual input are imported into the reasoning system to establish the logical relationships of the construction process. Construction time parameters and spatial resource requirements are then automatically calculated using MySQL. Subsequently, the spatial layout and resource allocation data exported from the BIM model are compared to assess whether the space meets the project requirements. Finally, a construction schedule that satisfies the space constraints is generated. The method was validated through a case study, demonstrating its effectiveness in automatic schedule planning under human-computer interaction. This study introduces an innovative approach that considers spatial conflicts in the automatic scheduling process, improving planning efficiency and reducing the risk of spatial conflicts on construction sites.

Digital Technologies for Promoting Construction and Demolition Waste Management: A Systematic Review

The increasing concern about the environment has led to the necessity of ensuring efficient Construction and Demolition Waste Management (C&DWM) in the built environment. Despite the extensive research on C&DWM, the industry still faces significant challenges, including inefficiencies, high costs, and environmental impacts. Meanwhile, incorporating digital technologies (DTs) has emerged as a way to eradicate the challenges of C&DW. In response to the knowledge gap, in this research, we conducted a systematic literature review (SLR), incorporating bibliometric, text-mining, and content analysis to meet the research objectives. In total, 126 papers were retrieved from the Scopus database and transferred into VOSviewer to conduct the bibliometric analysis. The findings identified seven specific DTs, namely, blockchain, Internet of Things (IoT), Artificial Intelligence (AI), Machine Learning (ML), Robotics, Computer Vision (CV), and Building Information modeling (BIM). This study demonstrates that these technologies play a significant role in promoting efficient C&DWM in the construction industry. The study’s implication lies in its potential to guide industry stakeholders and policymakers in promoting the use of DTs and overcoming the barriers to their adoption, thereby facilitating more efficient and sustainable C&DWM practices. Finally, the findings of our research indicate possible future research directions for promoting DTs for C&DWM and eradicating the barriers to efficient implementation.

Technological advancements and the vision of a meta smart twin city

Recent digital advancements have led the construction industry to reassess its core principles. Critical issues such as construction site impacts, aesthetics, methodologies, and sustainability are under rigorous scrutiny. The challenges hindering the digital transformation of construction remain unclear. Addressing the technical questions of when, where, why, and how the industry is evolving is crucial, especially as digital operations become more prevalent compared to traditional methods.The “digital twin” concept has emerged as a key approach in shaping the industry's future. Integrating Building Information Modelling (BIM) with the Internet of Things (IoT) has enhanced project engagement, though challenges persist. Traditionally, a digital twin represents the construction process and its interactions. But it misses the transactional and experiential aspects that integrate users into the process. Technologies like blockchain and the metaverse, combined with the digital twin, offer insights into the future of construction projects. Municipalities that adopt digital twins and metaverse representations of their commercial activities throughout construction phases are likely to set future standards for societal specifications.As some specifications such as architectural designs should be grounded in the diverse aspirations and experiences sought by citizens. This paper aims to explore the ways digital twins, smart urban environments, blockchain technology, and other reality capture datasets contribute to the vision of digital and physical construction domains. It examines the interaction and convergence of new spatial constructs, highlight the critical role of data acquisition technologies, and present a comprehensive framework for user experience and the future of Meta Smart Twin Cities.