Search Results (1,842)

This study examined how mechanical, electrical, and plumbing (MEP) practitioners understand and apply quality and safety management in construction projects in Taiwan. It focused on the gap between what practitioners know about best practices and what they can carry out on site, defined here as the “Cognitive–Execution Gap.” A mixed-methods design was used, combining a questionnaire survey of 130 MEP practitioners with semi-structured interviews with six senior experts. Practitioners with MEP-related academic backgrounds scored significantly higher in professional knowledge and practice than those from unrelated fields, with mean differences of 0.87 and 0.78 points on a 5-point scale, respectively (both p < 0.001). In contrast, awareness of management optimization strategies was high and similar across all demographic groups. Interview findings suggest that schedule pressure, the lower organizational status of MEP compared with civil engineering, and persistent talent shortages prevent practitioners from applying the practices that they recognize as necessary. The results provide evidence consistent with a Cognitive–Execution Gap and suggest that bridging it requires organization-level reforms, including prospectively evaluated BIM-based coordination, clearer standard operating procedures and performance indicators, and structured mentorship programs to strengthen professional capacity in MEP engineering. Full article

Automated compliance checking (ACC) integrated with Building Information Modeling (BIM) requires regulatory texts that can be translated into machine-executable rules. Existing studies have largely focused on rule extraction techniques and ontology-based modeling within single jurisdictions, leaving the upstream question of regulatory readiness underexplored. This study introduces a clause-level framework for assessing the formalizability of building regulations and applies it to four documents covering accessibility and fire safety in the United Kingdom and Kazakhstan. The corpus was decomposed into 2361 enforceable clauses, classified using a ten-category semantic taxonomy, and evaluated against four formalizability criteria: explicit scope, measurable requirement, deterministic outcome, and design-stage data availability. Clauses were classified as formalizable only when satisfying all four criteria simultaneously. UK documents reached 85% formalizability for accessibility and 90% for fire safety, compared with 77% and 51% for the corresponding Kazakh standards. The largest gap was observed in fire safety, where the Kazakh corpus contained fewer BIM-oriented and spatially explicit checks and a higher share of clauses lacking evidential specification. The proposed framework supports clause-level diagnosis of regulatory automation readiness, and a four-stage roadmap links linguistic structure to digital maturity in both jurisdictions. Full article

Construction sectors in developing countries continue to experience disproportionately high fatality rates, largely due to reactive safety practices and the limited adoption of digital safety technologies. While Building Information Modeling (BIM) and the Internet of Things (IoT) offer significant potential for proactive safety management, their integrated application remains underexplored in resource-constrained contexts. This study examines stakeholder readiness to adopt IoT-enhanced BIM-based safety monitoring systems in large-scale infrastructure projects in Pakistan, including China–Pakistan Economic Corridor (CPEC) initiatives and the Barakahu Bypass project. An integrated Technology Acceptance Model–Technology–Organization–Environment (TAM–TOE) readiness framework is employed, wherein TAM-derived cognitive-motivational factors (Technology Awareness and Perceived Benefits) and TOE-derived contextual factors (Organizational Readiness and Perceived Barriers) are examined as joint predictors of Behavioral Intention (BI). Data were collected from 107 purposively sampled construction professionals using a structured questionnaire. The results indicate high attitudinal readiness (BI mean = 4.7; perceived benefits mean = 4.6) alongside moderate organizational readiness (mean = 3.4). Regression analysis reveals that perceived benefits (β = 0.42, p < 0.001) and technology awareness (β = 0.29, p = 0.003) are the strongest positive predictors of adoption intention. In contrast, perceived barriers exert a significant negative effect (β = −0.22, p = 0.022). The model explains 61.2% of the variance in behavioral intention. This study advances the literature by providing empirical evidence on stakeholder readiness for BIM–IoT safety adoption within construction management processes, estimated through a multiple regression model. It offers practical implications for policymakers and industry stakeholders seeking to accelerate data-driven decision-making and digital safety transformation in developing economies. Full article

Graph-based spatial analysis methods are widely used to evaluate accessibility, visibility, spatial hierarchy, and movement-related properties of architectural floor plans. However, these analyses are often conducted using standalone tools and separate simplified models, which can delay design feedback and introduce additional data preparation steps. This paper presents a BIM-embedded computational workflow for configuring, computing, and visualising spatial graph analyses within Autodesk Revit using Dynamo, Python scripting, and the Accessibility and Visibility Analysis (AVA) package. The contribution is not the development of new graph algorithms, but the documentation of a reproducible workflow that sequences existing tools, graph construction settings, metric configuration, spatial measure computation, and 2D/3D visual feedback within a modelling environment. The workflow is demonstrated through a two-storey residential case study and supports accessibility, visibility, centrality measures, visual step depth, shortest path, isovist, object visibility, and activity-based origin–destination analysis. Particular attention is given to incorporating vertical circulation connections into level-based accessibility graphs for selected cross-level movement analysis. Building on prior AVA–DepthmapX verification by the authors, the paper focuses on workflow transparency, reproducibility, and multi-level accessibility representation. The findings indicate that BIM-embedded spatial graph analysis can support iterative, performance-informed design evaluation. Full article

Large-scale WebGIS visualization of 3D building models is often constrained by large requested payloads, client-side memory pressure, and runtime state-parsing overhead. This study proposes a five-dimensional orthogonal decoupling framework and a 16-bit state-word-driven scheduling method for 3D building models. The Boundary-based Spatial Proxy–Geometric Detail–Component Complexity–Texture Appearance–Semantic Information (B-D-C-T-S) framework organizes model representations into five separately addressable and schedulable dimensions, covering spatial proxies, geometry, components, textures, and semantics. A compact 16-bit structured state word is used to represent runtime states and reduce dependence on repeated text-based state parsing, supporting fixed-offset bitwise decoding, exclusive-OR (XOR)-based differencing, constraint checking, and incremental updating. A centroid-assigned Home Tile strategy is further introduced to reduce redundant semantic payloads for cross-tile objects. The method was evaluated using a single-building BIM model and an urban-scale photogrammetric mesh dataset. Under the tested initial-view setting, staged decoupled loading reduced the first-screen requested payload by 93.1% compared with monolithic loading. State-word-based C-field extraction achieved an approximately 144-fold speedup over JSON deserialization and C-field lookup. The Home Tile strategy reduced the total semantic payload by 44.1% in the semantic-redundancy test. In the 1.12 GB first-screen memory test, state-word-driven D1 tile scheduling loaded only 22.7 MB of physical payload, with stable resident memory of approximately 88.1 MB. These results indicate that the proposed method supports object-level state representation, selective resource activation and scheduling, Home Tile semantic routing, incremental updating, and first-screen memory control within tiled Web3D pipelines. Full article

In recent decades, the introduction of e-procurement has profoundly transformed the methods of procuring goods, services, and works, redefining traditional procurement processes and significantly impacting global economic, operational, and regulatory dynamics. The construction sector has also been affected by this transition, which has altered the operating models of public procurement and favoured the adoption of digital tools aimed at more efficient, transparent, and automated process management. This study proposes a systematic literature review based on the analysis of 95 scientific contributions, with the aim of outlining the evolution of the e-procurement paradigm in the construction sector and identifying the main directions for research development. Despite the widespread dissemination of studies on the topic, it emerges that the actual maturity of e-procurement systems is still limited, often resulting in a logic of document dematerialization rather than full process digitalization. In this context, the review critically analyses the role of Building Information Modelling as an enabling factor for the evolution of e-procurement, exploring the potential of its integration into procurement flows. Particular attention is paid to the contribution of the Digital Building Logbook, an information tool capable of extending the value of data generated during the tender phase throughout the building’s entire life cycle, supporting advanced management and maintenance strategies. The results highlight how, despite the significant potential of integrating e-procurement and BIM, significant technological, regulatory, and cultural issues persist that limit its large-scale adoption. This underscores the need to develop shared and interoperable methodological approaches capable of transforming procurement from a document-based process to an integrated information system, oriented toward value creation throughout the entire life cycle of projects. Full article

Simulation technologies are widely used in the construction industry to analyze complex operations and evaluate project performance before physical construction begins. However, interpreting simulation outputs remains challenging due to the dynamic nature of construction activities and the difficulty of representing spatial and temporal changes using traditional numerical or textual outputs. To address these limitations, researchers increasingly integrate visualization technologies with construction simulation models to improve understanding, communication, and decision-making. Using the PRISMA methodology, this paper presents a systematic literature review of visualization technology applications in construction simulation during the building phase. A total of 118 relevant publications published between 2000 and 2023 are reviewed and analyzed. The findings reveal a strong relationship between visualization technologies and Building Information Modeling (BIM), Virtual Reality (VR), and game engine technologies. Autodesk Navisworks and Unity are identified as the most frequently used visualization platforms, with game engines showing increasing adoption in recent years due to their support for immersive and interactive environments. The reviewed studies are further categorized into six primary use cases: scheduling and planning, education and training, equipment management, safety management, workspace planning, and simulation validation and verification. The results also demonstrate increasing research interest in real-time visualization, AR/VR integration, and interactive simulation environments. Overall, the findings highlight the growing role of visualization technologies in improving construction project planning, communication, training, safety, and decision-making, while also identifying important future research directions related to interoperability, real-time interaction, and extensible visualization platforms. Full article

This study evaluates the adoption and efficacy of the 5th Dimension Building Information Modelling (5D-BIM) as a cost dimension for mega rail projects, extending the discussion beyond just technological implementation to consider broader policy and practical implications. The purpose of this article is to understand the governance context of 5D-BIM implementation for rail and transport projects and evaluate the effectiveness of the 5D-BIM framework as currently applied by conducting semi-structured interviews with key stakeholders. Drawing on semi-structured interviews with 22 stakeholders across government, industry, and technology providers, the research examines current 5D-BIM practices. While the primary focus of the research is 5D BIM implementations within the state of Victoria, Australia, which is currently experiencing a surge in rail projects, interviews were also conducted with additional stakeholders from international rail projects for context. The findings reveal fragmented adoption, varying levels of organisational maturity, and significant policy and implementation gaps, particularly in the role of government as the primary client of transport infrastructure. The results of the interviews emphasise the centrality of government and regulatory context in driving the adoption and implementation of 5D-BIM as the primary client of transportation infrastructure and identify actionable recommendations for policymakers and practitioners towards a more integrated approach to 5D-BIM in mega rail projects. While 5D-BIM demonstrates clear benefits in enhancing cost estimation, coordination, and decision-making, its effectiveness is constrained by the absence of clear standards, limited BIM literacy, and inconsistent regulatory guidance. This study provides one of the first empirical validations of the 5D-BIM governance framework, demonstrating that its success is driven less by technological capability and more by policy alignment, standardisation, and institutional leadership. 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

Construction projects depend heavily on manual labor; however, workforce productivity is frequently constrained by poor planning and communication. This paper proposes a methodological framework that combines Building Information Modeling (BIM) with the Lines of Balance (LOB) technique to estimate, allocate, and visually coordinate crews in repetitive building work. Using a Design Science Research approach, the study draws on a systematic review of 29 eligible studies that identified 23 processes for human resource planning and allocation. These processes are structured into five planning categories: scope and duration, structuring and quantification, resource estimation and allocation, schedule baseline, and cost baseline. BIM support is operationalized through seven high-utility BIM applications identified by expert assessment (RUI > 0.75), including phase planning, scheduling, site utilization planning, and cost estimation. The framework connects model-based quantity takeoff and productivity assumptions with LOB-based sequencing and crew assignment. This integration enables early detection of spatiotemporal overlaps and workload imbalances through consistent BIM–LOB visualization. The method was implemented and calibrated in two residential case studies (one covering 295 m² over 3 months and the other 3660 m² over 22 months), resulting in workforce plans comprising 10 workers across five crews and 72 workers across nine crews. An evaluation involving 31 professionals indicates a high perceived utility, particularly in reducing errors in quantity and productivity estimation (RUI = 0.90) and crew quantification (RUI = 0.88). Full article

The paradigm transition of the life cycle management of physical assets in the railway sector demands new maintenance models that imply the conventional predictive approaches to be surpassed. This paper proposes an innovative methodology that integrates Building Information Modelling (BIM) with predictive maintenance (PdM) systems to be applied to rolling stock and, in this way, be enhanced by Generative Artificial Intelligence (GenAI). The research focuses on the autonomous synchronisation of the Rolling Stock Digital Twin (DT). Unlike static BIM models, the proposed solution enables the use of GenAI algorithms to process continuous data streams from integrated sensors, allowing the digital model to evolve autonomously as physical wear occurs. In this framework, GenAI (via Generative Adversarial Networks—GANs) is essential for data augmentation, enabling the simulation of rare “long-tail” failure events that are scarce in real-world historical data. By synthesising these degradation scenarios, the model learns complex mechanical collapse patterns that otherwise would be ignored by traditional PdM approaches. GenAI is employed to synthesise degradation scenarios, perform real-time parametric updates within the IFC (Industry Foundation Classes) schema, and optimise maintenance workflows. The application of this framework demonstrates a significant reduction in diagnostic latency and optimises the rolling stock’s operational life cycle by automating updates and reducing the need for manual data entry. This study concludes that the convergence among BIM, PdM, and GenAI establishes a robust framework for railway fleet management. While the current validation focuses on bogie systems using Random Forest and LLMs, it paves the way for a future Industrial Metaverse where immersive diagnostics can be integrated into the maintenance lifecycle. Full article

Lightweighting Building Information Modeling (BIM) models for digital-twin applications requires balancing aggressive geometric reduction with component-level engineering tolerances and mesh usability. Most geometric simplification pipelines apply uniform ratios or hand-tuned heuristics, which struggle to accommodate the strong heterogeneity of BIM components in functional role, geometric complexity, and detail distribution. End-to-end learning-based simplification can be adaptive, but it often entangles decision-making with geometric editing, making engineering constraints difficult to enforce and audit. We present Semantic-Geometric Co-driven Adaptive Budget Estimation and Reduction for BIM (SABER-BIM), which formulates lightweighting as a component-level face-budget allocation problem. Conditioned on Industry Foundation Classes (IFC) types and structure-sensitive geometric descriptors, SABER-BIM predicts target face counts for individual components and then meets a user-specified global budget through global scaling. The predicted budgets are executed by a robust geometric backend (e.g., quadric error metrics, QEM), yielding an auditable and easily deployable pipeline. To address the absence of direct supervision, we introduce an offline pseudo-ground-truth procedure that searches for the minimum feasible target face count for each component under semantic-aware tolerance and mesh-validity constraints. Experiments on the IFCNet dataset show that SABER-BIM allocates budgets more effectively under identical global constraints, improving stability in both geometric error control and engineering usability. Full article

Despite the operational phase being the most cost-intensive in a building’s lifecycle, Facility Management (FM) resource optimization continues to face challenges due to fragmented and low-structured data. Building Information Modeling (BIM) offers a centralized data environment, but interoperability gaps persist between design-oriented BIM models and operational Computerized Maintenance Management Systems (CMMSs). This paper presents a scalable, standards-based methodology for BIM-CMMS integration based on the extension of Industry Foundation Classes (IFCs) and the enrichment of FM data. The proposed Python-based application leverages the open-source IfcOpenShell library to inject custom, FM-specific Property Sets (Psets), including asset condition, criticality, and maintenance schedules, directly into IFC entities. The approach transforms standard IFC files into data-rich Asset Information Models (AIMs) without relying on proprietary middleware. The methodology was validated through two residential building case studies. IFC models were successfully checked through the buildingSMART validation service, providing full interoperability across multiple IFC-compatible platforms. Integration with OpenMAINT automatically generates a complete asset database, minimizing manual data entry and reducing inconsistencies. The results confirm the feasibility of a repeatable open-standard workflow. The future development is the definition of a functional/cognitive DT, with the scope of improving the lifecycle BIM model quality and enhancing the efficiency of facility operations. 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

For a developing country like India, data and information management remains a critical challenge in construction projects. This can be attributed to fragmented workflows, multiple digital platforms, and limited interoperability between project and enterprise systems. This study investigates current practices and challenges in data and information exchange within the Indian construction industry. It further examines the potential of Building Information Modeling (BIM) and Enterprise Resource Planning (ERP) integration to address these challenges. A questionnaire survey was conducted among construction professionals to capture organizational data management strategies, tools used for information exchange, BIM maturity levels, and commonly adopted BIM, Common Data Environment (CDE), and ERP platforms. Descriptive statistics and thematic analysis were applied to interpret the survey responses. The findings reveal that BIM and ERP integration was perceived by respondents to improve information accessibility, document traceability, and coordination efficiency, particularly where centralized CDE platforms were consistently adopted, when supported by standardized data formats, clear workflows, and targeted capacity-building initiatives within organizations. Full article