Search Results (49)

The construction industry is recognised globally as one of the most hazardous sectors. Effective hazard management necessitates identifying and communicating these risks early in the project lifecycle. Construction Hazard Prevention through Design (CHPtD) addresses this by incorporating safety information into the design phase that is often cumbersome and heavily reliant on reviewer expertise. The present work enhances hazard recognition and visualisation by automating the process using computational intelligence and building information modelling, aligning with the theoretical framework of CHPtD. The proposed tool provides detailed hazard information, including the nature of the hazard, its causes, and potential resolutions, empowering designers to make informed decisions and mitigate risks proactively. The tool’s performance is evaluated using a confusion matrix, demonstrating promising results with an overall accuracy of 84.77% and a Kappa coefficient of 0.83. While the tool shows strong performance in identifying several hazard classes, further refinement is needed to improve its ability to detect catastrophic events and manage traffic-related hazards. Full article

The development of Building Information Modeling (BIM) and Generative Design (GD) methods supported by artificial intelligence opens up new possibilities in the field of urban planning analyses and the verification of land-use compliance with local regulations. The aim of this study was to assess the potential of the Autodesk Forma Site Design environment, which utilizes BIM technology and generative methods, in streamlining planning processes, using the example of an analysis of the compliance of existing development with local regulations. The research was conducted based on a case study of selected plots located in the Polish city of Włocławek, covered by the 2004 Local Spatial Development Plan (LDSP). The scope of work included the analysis of planning documents, parametric modeling in Autodesk Forma Site Design, and the generation of development variants using the Archistar and One Click LCA Generative Design plugins. The results indicate that Generative Design tools can effectively support the early stages of urban planning analyses, enabling the rapid generation and comparison of land-use variants as well as a preliminary assessment of their compliance with planning regulations. At the same time, significant technological limitations were identified, including the lack of full determinism of parameters, difficulties in the automatic interpretation of complex planning regulations, and the need for manual correction of results. Consequently, the current level of development of generative tools allows for a partial streamlining of planning processes, but does not yet provide a basis for the full automation of verifying the compliance of land-use plans with local regulations. Full article

Addressing the prevalent issues of scattered data sources, reliance on multi-software collaboration, and low integration efficiency between Building Information Modeling (BIM) and Life Cycle Assessment (LCA) in current building life cycle carbon emission accounting, this study aims to construct a BIM-driven, data-traceable automated method for building life cycle carbon accounting. This paper proposes a life cycle carbon accounting framework based on Revit secondary development. By defining unified data mapping rules and constructing a scalable localized carbon emission factor database, this framework achieves a seamless workflow from BIM model information extraction and intelligent factor matching to phased accounting and report generation. Taking an office building in Nanning as an empirical case study, the results indicate that the operational stage and the building material production stage are the primary emission sources, accounting for 78.82% and 24.13% of the total emissions, respectively; the transportation stage accounts for 1.68%; the construction stage accounts for 0.40%; and the demolition and recycling stage exhibits negative emissions of −3.53% due to material recovery benefits. The accounting results of the developed plugin exhibit a relative error of 6.67% compared to traditional methods, and the robustness of the accounting framework is verified through uncertainty analysis. Sensitivity analysis further reveals that the grid emission factor, key material factors, and building design service life are the core variables affecting carbon emissions. The contribution of this study lies in proposing an operable and scalable BIM-LCA integrated solution. Its practical value resides in providing a real-time data feedback tool for low-carbon optimization during the building design stage, as well as offering a highly transparent methodological reference for carbon accounting in engineering practice, thereby supporting data-driven decision-making in the pursuit of sustainable urban development. Full article

Building Information Modelling (BIM) offers a pivotal opportunity to automate Life Cycle Assessment (LCA) within the Architecture, Engineering, and Construction (AEC) industry. However, seamless integration is persistently hindered by a semantic gap, a critical misalignment between the object-oriented, geometric definitions of BIM and the process-based material data required by Life Cycle Inventory (LCI) databases. This paper presents a comprehensive review of data interoperability challenges and evaluates advanced methodologies designed to bridge this divide, moving beyond simple tool comparison to analyse structural integration barriers. Through a systematic review of 124 primary studies published between 2010 and 2025, this research inductively derives the BIM-LCA Interoperability Triad. This framework analyses causal dependencies across three dimensions, including Semantic and Ontological Structures, Workflow and Temporal Integration, and System Architecture and Interoperability. Furthermore, by establishing a comparative challenge–solution matrix, the analysis reveals a maturity paradox in current methodologies. While semi-automated commercial plugins dominate practice due to accessibility, they frequently function as opaque black boxes with limited transparency. Conversely, advanced approaches utilising Semantic Web technologies and Machine Learning demonstrate superior capability in resolving terminological mismatches but currently face significant barriers regarding infrastructure and expertise. This study contributes a novel theoretical model for understanding integration failures. It concludes that future research must pivot from static schema mapping towards AI-driven semantic healing, dynamic Digital Twins, and explicit system boundary harmonisation to achieve truly automated, context-aware environmental assessments and support whole-life circularity. Full article

This paper presents the concept and implementation of the BIM–CARVER tool, which integrates the CARVER matrix (Criticality, Accessibility, Recuperability, Vulnerability, Effect, Recognizability) with an open BIM environment based on the IFC standard. Originally developed by the US military for target analysis, the CARVER matrix has evolved into a defensive tool for protecting critical infrastructure. Traditionally, physical security assessments of buildings are performed manually, separately from the digital model, contradicting the principles of Security by Design, which assume that security aspects should be taken into account at the early stages of design. As part of research conducted in accordance with the Design Science Research methodology, a plugin for the Bonsai platform (BlenderBIM) was developed, enabling the assignment of vulnerability assessments to individual elements of the IFC model according to six CARVER criteria on a scale of 1–10, the visualization of results directly in the modeling environment, and the generation of security reports in HTML format. The tool was validated on a set of ten building models of varying purpose and complexity. The results confirmed the effectiveness of the tool in systematically identifying and classifying building elements into four risk categories: critical, important, significant, and insignificant. The developed semi-automated solution supports designers and security specialists in the proactive identification of threats and enables the comparison of design variants in terms of the aggregated risk level, contributing to the implementation of Security by Design principles in design practice. By reducing the need for costly security retrofits and enabling resource-efficient design decisions, the proposed approach also contributes to the sustainability objectives in the built environment. Full article

Green building rating systems (GBRS) (e.g., LEED and BREEAM) assess sustainability in the built environment but require extensive data collection and processing. In this context, digitalization strategies, such as building information Modeling (BIM), enable centralized data management throughout the building’s life cycle. This study presents a PRISMA-based systematic literature review (SLR) of BIM-GBRS integration methods, identifying 83 articles and 13 reviews. The analysis is structured around three key phases defined to enable a systematic comparison of the existing approaches. Phase 1, “Data acquisition”, involves collecting the values of the investigated parameters either from the BIM model or through analysis software (e.g., Insight, One Click LCA) grouped into eight categories. Phase 2, “compliance verification”, focuses on comparing collected data with GBRS requirements using manual or automated tools (e.g., Dynamo). Phase 3, “optimization”, involves improving alternative design scenarios using tools such as plug-ins and MATLAB-based algorithms (e.g., NSGA-II, DWKNN). Emerging digital technologies (e.g., AI, digital twins, IoT) are analyzed to enable automated workflows, while interoperability is examined by distinguishing format-based (e.g., gbXML, IFC) and tool-based (e.g., APIs, VPL) approaches. The study identifies fragmented and limited interoperability in BIM-GBRS integration, highlighting the need for an automated end-to-end framework to support sustainability in the construction sector. Full article

Embodied-carbon accounting is increasingly required at the early design stage to guide material and construction choices during design iterations. However, many life-cycle assessment (LCA) workflows and centralized building information modeling (BIM)–LCA plugins still rely on fragmented data, non-transparent mapping rules, and limited cross-project reuse, which slows rapid iteration. This study develops an open and traceable embodied-carbon assessment workflow driven by BIM object geometry and semantic attributes and demonstrates it through a single case study, enabling automated accounting for the A1–A3 stages from model input to result reporting. The framework is implemented as a Revit add-in prototype connected to an open-data platform. It uses assemblies as standardized assessment units, applies configurable rule-based mapping, and performs unit normalization to link model quantities with carbon factors. A single three-story brick–concrete residential building in Wuhan with an LoD 300 model is used as the sole validation case to demonstrate workflow feasibility, report coverage, and time metrics. The case yields an A1–A3 embodied-carbon intensity of approximately 333 kgCO₂ e/m², dominated by the structural system. Rule mapping achieves 82% coverage within the defined accounting scope. Compared with manual workflows (290–380 min), first-time accounting is reduced to 83–98 min and further to within 30 min when assemblies and rules are reused. Contribution decomposition shows a concentrated pattern and supports traceability from assemblies to material types. Overall, within the tested scope, the Revit-based prototype provides efficient and verifiable embodied-carbon feedback for early-stage design. Full article

This study addresses the challenge of identifying heavy Building Information Modeling (BIM) library components that disproportionately degrade model performance. While BIM has become standard in the construction industry, heavy components characterized by excessive geometric complexity, numerous instances, or inefficient optimization—cause extended file loading times, interface lag, and coordination difficulties, particularly in large cross-industry projects. Current identification methods rely primarily on designer experience and manual inspection, lacking systematic evaluation frameworks. This research develops a multi-criteria evaluation method based on Multi-Criteria Decision Analysis (MCDA) that quantifies component performance impact through five weighted criteria: instance count (20%), geometry complexity (30%), face count (20%), edge count (10%), and estimated file size (20%). These metrics are aggregated into a composite Weight Score, with components exceeding a threshold of 200 classified as requiring optimization attention. The method was implemented as HeavyFamilies, a pyRevit plugin for Autodesk Revit featuring a graphical interface with tabular results, CSV export functionality, and direct model visualization. Validation on three real BIM projects of varying scales (133–680 families) demonstrated effective identification of heavy components within 8–165 s of analysis time. User validation with six BIM specialists achieved 100% task completion rate, with automatic color coding and direct model highlighting particularly valued. The proposed approach enables a shift from reactive troubleshooting to proactive quality control, supporting routine diagnostics and objective prioritization of optimization efforts in federated and multi-disciplinary construction projects. Full article

State Departments of Transportation (DOTs) face challenges with traditional bridge inspections that are time-consuming, inconsistent, and paper-based. This study focused on an existing research gap regarding automated methods that streamline the bridge inspection process, prioritize maintenance effectively, and allocate resources efficiently. Thus, this paper introduces a digitalized bridge inspection framework by integrating Building Information Modeling (BIM) and Business Intelligence (BI) to enable near-real-time monitoring and digital documentation. This study adopts a Design Science Research (DSR) methodology, a recognized paradigm for developing and evaluating the innovative SmartBridge to address pressing bridge inspection problems. The method involved designing an Autodesk Revit-based plugin for data synchronization, element-specific comments, and interactive dashboards, demonstrated through an illustrative 3D bridge model. An illustrative example of the digitalized bridge inspection with the proposed framework is provided. The results show that SmartBridge streamlines data collection, reduces manual documentation, and enhances decision-making compared to conventional methods. This paper contributes to this body of knowledge by combining BIM and BI for digital visualization and predictive analytics in bridge inspections. The proposed framework has high potential for hybridizing digital technologies into bridge infrastructure engineering and management to assist transportation agencies in establishing a safer and efficient bridge inspection approach. Full article

Water pumping stations are essential components of national water infrastructure, yet their construction involves complex, high-risk processes, and traditional risk management approaches often show significant limitations in practice. To address this challenge, this study proposes a Building Information Modeling (BIM)-based approach that integrates structured risk information into an interactive nD BIM environment. We first developed an extended Risk Breakdown Matrix (eRBM), which systematically organizes risk factors, assessment levels, and causal relationships. This is linked to the BIM model through a customized BIM–risk integration framework. Subsequently, the framework is further implemented and quantitatively validated via a Navisworks plug-in. The system incorporates three core components: (1) a structured risk information model, (2) a visualization mechanism for dynamic, spatiotemporal risk representation and (3) risk influence path analysis using the Decision-Making Trial and Evaluation Laboratory–Interpretive Structural Modeling (DEMATEL–ISM) method. The plug-in allows users to access risk information on demand and monitor its evolution over time and space during the construction process. This study makes contributions by innovatively integrating risk information with BIM and developing a data-driven visualization tool for decision support, thereby enhancing project managers’ ability to anticipate, prioritize, and mitigate risks throughout the construction lifecycle of water pumping station projects. Full article

Preservation of Cultural Heritage (CH) demands precise and comprehensive information representation to document, analyse, and manage assets effectively. While Building Information Modelling (BIM) facilitates as-is state documentation, challenges in semantic interoperability of complex cultural data often limit its potential in heritage contexts. This study investigates the integration of BIM tools with the buildingSMART Data Dictionary (bSDD) platform to enhance semantic interoperability for heritage assets. Using a proof-of-concept approach, the research focuses on a historic tenement house in Tarnów, Poland, modelled with the IFC schema standard and enriched with the MIDAS heritage classification system. The methodology includes transforming the classification system into bSDD data dictionary, publishing thesauri for components, materials, and monument types, and semantic enrichment of the model using Bonsai (formerly BlenderBIM) plugin for Blender. Results demonstrate improved consistency, accuracy, and usability of BIM data for heritage preservation. The integration ensures detailed documentation and facilitates interoperability across platforms, addressing preservation challenges with enriched narratives of cultural significance. This method supports future predictive models for heritage asset conservation, emphasizing the importance of data quality and interoperability in safeguarding shared cultural heritage for future generations. Full article

Electrical engineering design in construction projects often faces challenges such as inefficient model connectivity, prolonged drawing reviews, and complex cable layout optimization, especially when high-precision Building Information Modeling (BIM) models are required. These issues hinder efficiency and accuracy in electrical system design. Recent studies emphasize the need for more efficient workflows in BIM-based electrical engineering design. Traditional tools rely on manual inputs and high-precision models, causing inefficiencies in time and resources. Previous research highlights the importance of automating processes like cable routing and system validation, but few address intelligent optimization or automation integration in BIM systems. This study develops a comprehensive system for BIM-based electrical engineering design. The proposed Revit plugin generates optimized results without the need for high-precision models. Key stages are detailed, including rapid model connection, streamlined drawing review, and advanced cable optimization. Validation in real-world projects shows that the system improves design and construction efficiency, enhances cable installation quality, and achieves substantial cost savings. The system delivers dual benefits of increased productivity and superior quality in electrical construction projects, marking a significant advancement in BIM-based electrical engineering design. Full article

Building information modeling (BIM) has revolutionized integrated planning by optimizing costs, schedule, and material use. However, building energy modeling (BEM) remains underutilized in early design stages due to interoperability challenges between BIM and BEM tools. This study addresses these challenges by exploring standardized exchange requirements and introducing a novel toolchain that bridges BIM and BEM workflows. In the BIM2IndiLight project, over 400 standardized properties for daylighting, artificial lighting, and façade systems were validated, revealing the advantages and limitations of parameter standardization. Building on these insights, the BIM2BEM-Flow project developed a three-step toolchain that efficiently manages project- and company-specific properties, defines mapping rules, and integrates parameters via a BIM plugin for validated IFC export. The results demonstrate that combining standardized properties with a flexible, workflow-driven toolchain significantly enhances data exchange and interoperability between BIM and BEM. This integrated approach supports early-stage energy performance optimization and offers a promising pathway toward more efficient design processes in the AECO industry. Full article

With the development of drone and image recognition technologies, using drones to capture images for engineering structural damage detection can replace inefficient and unsafe manual maintenance inspections. This paper focuses on the pairing method between drone devices and the BIM components of large buildings, with Revit’s secondary development serving as the technical approach. A plugin for pairing drone images with BIM components is developed. The research first establishes the technical scheme for pairing drone images with BIM models. Then, the positional and directional information of the drone images are extracted, and a reference coordinate system for the drone’s position and image capture orientation is introduced. The transformation method and path from the real-world coordinate system to the Revit 2023 software coordinate system are explored. To validate the interactive logic of the transformation path, a pairing plugin is developed in Revit. By employing coordinate conversion and Revit family loading procedures, the relative position and capture orientation of the drone are visualized in the 3D BIM model. The plugin uses techniques such as family element filtering and ray tracing to automatically identify and verify BIM components, ensuring the precise matching of drone images and BIM components. Finally, the plugin’s functionality is verified using a high-rise building in Wuhan as a case study. The results demonstrate that this technological approach not only improves the efficiency of pairing drone images with models in building smart maintenance but also provides a fast and reliable method for pairing drones with BIM systems in building management and operations. This contributes to the intelligent and automated development of building maintenance. Full article

A visual deformation prediction method was proposed to improve the accuracy and visualization of the surrounding rock deformation prediction in tunnel construction, combining the Variational Modal Decomposition (VMD) and Bidirectional Long- and Short-Term Memory (BiLSTM) network. Based on the VMD method to decompose the measured data of tunnel surrounding rock deformation, the BiLSTM model was used to predict the final deformation value. The prediction results were also embedded into the tunnel’s Building Information Modeling (BIM) as plug-ins, and the data were visualized through graphs and color warnings. Taking the measured data of the arch settlement of the Loushan tunnel as an example, the results showed that the prediction results were more consistent with the measured situation, and the visualization expression could effectively warn of the risk of vault settlement in the construction stage. This study realized the combined use of surrounding rock deformation prediction and BIM technology, which could be used as a reference for similar projects. Full article