Search Results (2,858)

The rehabilitation of aging educational buildings has become increasingly important in the context of sustainable campus development and adaptive reuse of existing infrastructure. This study proposes an integrated BIM-based framework for the rehabilitation of underutilized academic spaces through the combined application of Building Information Modeling (BIM), biophilic interior design principles, and Artificial Intelligence (AI) predictive modeling. The methodology was implemented in a case study involving non-functional areas within the Faculty of Aerospace Engineering at the National University of Science and Technology POLITEHNICA Bucharest. Autodesk Revit was employed to develop a parametric digital model of the existing structure, support spatial reconfiguration, and assess environmental and functional performance indicators throughout the rehabilitation process. To evaluate the effectiveness of the proposed framework, multiple performance criteria were considered, including spatial efficiency, daylight performance, material sustainability, acoustic quality, and user-perceived visual comfort. Furthermore, a synthetic dataset generated through parametric simulation was utilized to train and compare four machine learning algorithms (Multiple Linear Regression, Support Vector Regression, Random Forest, and Artificial Neural Networks) to predict user comfort based on spatial and environmental variables. The rehabilitation strategy resulted in an 18% increase in usable floor area, a 26% improvement in average daylight factor, a 25% increase in renewable material utilization, and a 38% reduction in estimated acoustic reverberation time. Simultaneously, the predictive modeling revealed that the Artificial Neural Network (ANN) provided the highest accuracy (R² = 0.91) in capturing the non-linear relationship between biophilic design elements and perceived interior quality. By integrating Gilbreth’s principles of cognitive ergonomics, the AI framework actively prevents the rigid, purely quantitative optimization associated with “Digital Taylorism, The findings demonstrate that the proposed BIM-integrated rehabilitation framework can support both technical optimization and user-centered environmental enhancement in educational facilities. The study contributes a transferable digital methodology for sustainable academic building transformation, combining geometric precision, predictive environmental performance assessment, and human-centered design principles within a unified rehabilitation workflow. Full article

The construction industry in Jordan faces significant economic and environmental challenges due to high material costs, fluctuating market prices, and the continued reliance on a linear economy model that prioritizes material extraction, consumption, and disposal over reuse and recycling. These challenges contribute to substantial construction waste generation and hinder the transition toward a Circular Economy (CE). Therefore, this study aimed to develop a framework for managing construction waste during the construction phase of residential building projects in Jordan and to facilitate the adoption of circular practices within the construction sector. A questionnaire survey was administered to 31 experts, and the collected data were analyzed using the Relative Importance Index (RII) and the Analytic Hierarchy Process (AHP). Subsequently, the proposed framework was evaluated through a three-round Delphi study involving an independent panel of experts. The results identified the principal barriers to implementation as the low demand for reused or recycled materials, limited stakeholder awareness, and difficulties in material disassembly. The findings further revealed that applying visual management and 5S techniques to improve site efficiency, implementing Building Information Modeling (BIM) for material and component mapping throughout the building life cycle, and providing tax incentives and grants for recycled materials were among the highest-ranked sub-strategies for supporting circular practices and minimizing construction waste. The Delphi evaluation demonstrated strong expert consensus regarding the framework’s applicability and practicality, indicating that it provides a structured, expert-informed approach that may assist policymakers and construction practitioners in promoting circular practices and reducing construction waste in Jordan. In addition, the framework has the potential to support Jordan’s Vision 2025 and contribute to the achievement of the Sustainable Development Goals (SDGs). Full article

Additive manufacturing (AM) is applied in sustainable architecture and Construction 4.0 because it can support design flexibility, mass customization, material efficiency, and reduced reliance on conventional formwork. Prior reviews often addressed either construction applications or broader digital transformation, leaving the intersection of AM, construction sustainability, digital technologies, and lifecycle performance underexplored. This study conducts a systematic and bibliometric review of literature retrieved from Scopus and Web of Science covering the period from January 2016 to January 2026. The review protocol followed SPAR-4-SLR principles and PRISMA 2020 guidelines, with 58 records retained for analysis. Bibliometric and thematic analyses identified a marked rise in publication activity after 2021 with four major research themes: material development and innovation, digital fabrication and process control, lifecycle assessment and circularity, and digital integration and project implementation. Construction 4.0 technologies, including BIM, digital twins, automation, and robotics, were the most frequently represented digital enablers. The review further identifies future research opportunities and outlines a proposed conceptual pathway toward Construction 5.0. This pathway connects materials, robotics, lifecycle performance, and human-centered priorities as a future research agenda. Overall, this study contributes to a more integrated understanding of how AM can advance sustainable, digitally enabled, and human-centered construction practice. Full article

Purpose: This study examines the preparedness of the Ghanaian construction workforce for Industry 5.0 by assessing digital readiness, identifying skill gaps, and proposing human-centred upskilling strategies. Design/Methodology/Approach: A qualitative approach was adopted, using six focus group discussions with 32 construction professionals from Accra and Kumasi. Participants were selected using purposive and snowball sampling, while data were analysed thematically. Findings: Four major themes emerged: digital readiness, skill gaps, upskilling strategies, and human–machine collaboration. The findings showed that digital readiness was uneven across roles, with design and managerial professionals demonstrating higher exposure to digital tools than site-based workers and supervisors. Six key barriers were identified: limited BIM competence, low digital literacy, poor technological infrastructure, weak organisational support, inadequate structured training, and resistance to technological change. Three upskilling priorities were also identified: role-specific digital training, continuous professional development, and inclusive training models. Originality: The study provides empirical evidence on Industry 5.0 workforce readiness within a developing-country construction context. Practical Implications: The findings support stronger CPD systems, inclusive training programmes, and collaboration among industry, government, academia, and professional bodies. Research Limitations: The study was limited to 32 professionals in Accra and Kumasi; therefore, the findings are context-specific. Full article

Integratingartificial intelligence (AI), the Internet of Things (IoT), and Building Information Modeling (BIM) holds considerable promise for modernizing construction management, yet a unified real-time framework connecting these technologies for heavy civil earthmoving remains lacking. This paper presents BIM-iDT, a BIM-Integrated Digital Twin framework that couples multi-source IoT sensing with an IFC-based BIM model to enable intelligent fleet coordination and automated progress control. The research follows a design-science methodology comprising framework formulation, modular development, field deployment, and multi-project validation. The framework comprises a heterogeneous sensor fusion layer aligning GPS, IMU, fuel-consumption, and LiDAR data within the BIM coordinate system; a spatio-temporal graph attention network (ST-GAT) that recognizes equipment states and predicts short-horizon productivity by modeling fleet-level spatial dependencies; a temporal point cloud differencing module that quantifies cut/fill volumes against BIM design surfaces; and a constrained multi-objective evolutionary optimizer (CMOEO) that generates Pareto-optimal dispatch plans balancing fuel, cycle time, utilization, and schedule adherence. Validation on a highway project with instrumented machines shows that ST-GAT achieves a macro-averaged F1 of 0.943, volume MAPE stays below 3%, and CMOEO reduces fuel consumption by 12.6% and cycle time by 9.3% while maintaining schedule adherence above 96%, yielding an estimated 168-ton CO₂ emission reduction. End-to-end latency averages 600 ms, satisfying real-time requirements. Cross-project transfer experiments on a secondary dam construction site further confirm framework generalizability, establishing BIM-iDT as a scalable paradigm for AI-and-IoT-enabled smart construction in infrastructure engineering. Full article

The rapid development of Heritage Building Information Modelling (HBIM) has transformed digital models of historic buildings from design-support tools into long-term information assets used for documentation, conservation, and heritage management. Despite their growing importance, issues related to copyright protection, intellectual property rights, and data exchange remain insufficiently addressed in both research and professional practice. This study examines the legal status of HBIM models under European Union, especially Polish, copyright law and identifies challenges associated with licensing and interoperability in BIM environments. The research combines a doctrinal analysis of copyright legislation, a review of BIM and HBIM literature, an examination of information management standards, and a case study of an HBIM project developed for a listed historic property of the University of Wrocław. The findings indicate that HBIM models may qualify as copyright-protected works, most often of a joint authorship nature, requiring clear regulation of economic rights, derivative works, and model updates throughout the lifecycle of a heritage asset. The study also reveals a gap between technical and legal interoperability, as the IFC format does not consistently preserve information concerning authorship, licensing conditions, and revision history during data exchange. The results highlight the need to integrate copyright considerations into contractual arrangements, Common Data Environment (CDE) management, and metadata structures to support the lawful and sustainable long-term use of HBIM models in cultural heritage conservation. Full article

A persistent barrier to BIM-based whole-life carbon assessment (WLCA) and circularity assessment is uncertainty whether and to what extent exchanged Industry Foundation Classes (IFC) models contain relevant information needed to parameterise inventory inputs. Without explicit readiness checks, missing or generic semantics may only become apparent during dataset mapping, leading to reliance on undocumented assumptions. This paper proposes an early-stage framework for assessing the information exchange readiness of IFC building models for WLCA inventory preparation and selected circularity-oriented interpretation. The framework structures checks into progressive levels: L1 element identification and classification, L2 geometry and quantity availability, and L3 material definition and property assignment, producing coverage metrics and categorical issue records. L4a and L4b are defined as conceptual extensions toward broader decision-support information for whole-life carbon reporting and end-of-life management. Prototype implementation reports information gaps affecting element inclusion, including incomplete property definitions, assignments, material specifications, and missing quantity data. To support fairer comparison across heterogeneous element subcategories, based on the Royal Institution of Chartered Surveyors (RICS) Whole Life Carbon Assessment 2.0 standard, the framework applies assessment relative to what is relevant for each of the subcategories. The study indicates that transparent, level-based IFC exchange-readiness assessment can support more traceable WLCA inventory preparation and circularity-oriented interpretation by making unmet information requirements explicit. Full article

Construction cost estimation often relies on subjective expert judgment, which introduces variability and inconsistency. Standardizing data and procedures can improve reliability and enable repeatable workflows. This research investigates how price lists used for public construction can be semantically linked to Building Information Modeling (BIM) via the Industry Foundation Classes (IFC) standard to support objective, repeatable, semi-automated model-to-cost estimation. By an inductive case-based design, the work uses Veneto Region price list and maps selected cost items to IFC properties. Six representative price list items (slabs, partition walls, plasterboards, plasters, doors, and windows) are examined to identify discriminating parameters (e.g., material, thickness, dimensions, fire rating) that are mappable to IFC entities and property sets. The methodology distinguishes primary charges from surcharges, then assesses the model-ability of parameters and their semantic coherence within BIM’s object-based paradigm. Findings show that through formalization and standardization of cost item characteristics via IFC properties, the approach reduces subjectivity, enabling structured and objective matching and laying the groundwork for future automated workflows. Limitations are discussed, including incomplete representation of some cost-driving attributes, reliance on naming conventions, and opportunities associated with Digital Product Passport implementation (DPP). Full article

Building Information Modeling (BIM) usually represents a building as a static snapshot of the model’s state. Dynamic extensions, such as Internet of Things(IoT)-enabled sensing or immersive visualization, already exist, but the underlying data model remains state-based. The Industry Foundation Classes (IFC) standard does not define a formal mechanism that would link the same physical element across successive phases of a building’s life cycle. Design, construction, and operation are recorded in separate IFC files, and the same element is assigned different Globally Unique Identifiers (GUIDs) in each. The result is fragmentation of the element’s identity, loss of the history of property changes, and the inability to formulate cross-phase queries. This paper proposes the BIM-Phase ontology based on the fundamental Descriptive Ontology for Linguistic and Cognitive Engineering (DOLCE) ontology, which solves this problem by introducing a distinction between a building element as an endurant and its life cycle phases as perdurants. The ontology comprises nine classes, six object relations, and six axioms expressed in Web Ontology Language 2 Description Logic (OWL 2 DL). Phase properties and relations are represented using a reification pattern, which maintains full compatibility with the expressiveness of OWL 2 DL. The ontology was validated using an example of a single-family residential building developed in Autodesk Revit. Three structural elements (external wall, floor slab, and column) were tracked across three phases of the life cycle. Eight competency questions covering scalar, constitutional, and mereological changes were defined and mapped to ontology constructs, confirming that the BIM-Phase enables the recording of changes and the formulation of cross-phase queries that are impossible in classic IFC. All eight questions were answered correctly on the published knowledge graph, and the HermiT reasoner confirmed the logical consistency of the model. The findings show that preserving element identity across phases requires only a minimal ontological layer on top of existing standards. We recommend introducing persistent, phase-independent identifiers of building elements alongside IFC GUIDs, as this single change enables full lifecycle change tracking. Full article

The bearingless induction motor (BIM) relies on accurate displacement feedback to maintain stable magnetic suspension, but sensor faults, degradation, and noise can distort feedback and induce transients during branch switching. This paper proposes a confidence-fusion-based fault-tolerant displacement measurement method for the BIM suspension feedback chain. A four-channel asymmetric redundant sensor configuration is developed, and channel state evaluation functions are constructed from sampling-difference terms and geometric-consistency residuals. A decreasing Sigmoid mapping with first-order smoothing generates continuous confidence coefficients to represent channel health. Combined with discrete fault flags of the primary channels, four reconstruction branches, AB, BC, AC, and CD, are adaptively weighted to obtain the reconstructed displacement, which is connected to the original suspension controller through a smooth feedback access mechanism. A MATLAB/Simulink closed-loop suspension model is used to evaluate the method under fault-free operation, an abrupt fault of primary channel A, simultaneous and sequential faults of primary channels A and B, abrupt and gradual degradation, constant bias, intermittent signal dropouts, and noise disturbance of primary channel B. Results show that the method identifies abnormal primary channels, redistributes reconstruction weights according to sensor conditions, and maintains a fallback path through the CD branch under dual-primary-channel failure. Under channel-B degradation, the confidence coefficient tracks the deterioration and supports the subsequent AB-to-AC branch transfer, whereas under noise disturbance, the fault flag remains inactive and unnecessary branch switching is avoided. The method improves feedback continuity without changing the main suspension controller. Full article

In the current Architecture, Engineering, Construction, and Operations (AECO) sector, the demand for a skilled workforce capable of responding to rapidly changing needs is increasing. However, academic programs are struggling to keep up with this transformation. The integration of Building Information Modeling (BIM) tools into design studios and the objective evaluation of the pedagogical outcomes of this process are not yet fully clear. This study develops a pedagogical evaluation framework to integrate professional BIM competencies into architectural design studio curricula. This framework aims to measure student competency development and guide the restructuring of academic programs for BIM-supported education. A mixed methodology was adopted in the research; utilizing a combination of purposive and convenience sampling techniques, the studio performances, submission processes, and survey data of 409 students studying in architecture and interior architecture departments over a four-year period were analyzed longitudinally using the developed measurement-evaluation model. The proposed framework serves to pedagogically grade students’ in-studio performance and to measure acquired competencies with structured criteria. The qualitative data obtained from the surveys were analyzed through thematic and content analysis. The research revealed that students possessed limited technical skills in BIM projects and experienced deficiencies in collaboration and data management. Furthermore, it determined that instructors’ lack of knowledge regarding integrating BIM into the curriculum negatively impacted students’ learning processes. This study recommended enhancing teacher training for BIM-supported education, improving collaboration and coordination skills, and aligning the curriculum with professional requirements. The findings provide a framework that not only better prepares students for professional life but also helps bridge the gap between education and industry. Through this framework, students’ competencies can be measured at the pedagogical level. Full article

Construction site fires caused by spatiotemporal overlaps between hot work (ignition sources) and combustible substances remain a critical concern. The traditional method identifies fire hazards based on the intersections among hot works and other works with combustible substances. However, the intersections between hot work and built elements containing combustible materials are ignored, which can also lead to fire accidents. In addition, the detection of such intersections relies on the computationally intensive proximity search from the ignition source to the potential combustible substances, resulting in a long-time calculation in large construction projects with the dynamic construction process. To address this limitation, this study proposes a voxel-based fire hazard identification method applicable to large 4D-BIM models, fast and accurately. By discretizing BIM into reusable LEGO voxels, both the construction activities and the building components can be mapped to the voxels, enabling a simultaneous intersection identification between ignition sources and both activities and BIM elements. In addition, voxel-based proximity searching is efficient, enabling a fast and accurate fire hazard identification. Validation tests demonstrate high accuracy with calculatable spatial error (maximum 0.57 m for 200 mm voxels) and superior efficiency (126–1368% faster than mesh-based methods). By reusing the voxelized BIM data, the speed can be enhanced by between 400% and 1975%. This method offers an efficient and reliable digital solution for proactive construction fire safety management in 4D-contexts. Full article

The growing adoption of prefabricated timber construction in Australia has highlighted persistent difficulties in integrating digital workflows between architectural design, structural engineering, and manufacturing. Although Building Information Modelling (BIM), Computer-Aided Design and Manufacturing (CAD/CAM), and Computer Numerical Control (CNC) technologies are increasingly used, fragmented software environments, inconsistent data exchange, and limited early manufacturer involvement continue to cause information loss, manual rework, and design-to-manufacturing workflow gaps. This study provides a PRISMA-informed structured review of design-to-manufacturing integration in prefabricated timber construction, focusing on workflow stages, software ecosystems, interoperability issues, and manufacturer-ready data requirements. Following PRISMA 2020 guidelines, 588 records from ScienceDirect and Web of Science were screened, resulting in 60 peer-reviewed studies. These were supplemented by 32 practice-based technical sources, including industry reports, software manuals, user guides, CNC/machinery manuals, and interface documents. The review maps current workflows for timber frames, trusses, and mass timber components, identifying recurring challenges such as fragmented responsibilities, insufficient data detail, incompatible software, repeated remodelling, and weak design-production continuity. Based on these findings, the paper proposes a conceptual digital integration framework emphasising early collaboration, shared parametric logic, and clearer manufacturer-ready data to support more reliable, resource-efficient, and sustainable design-to-manufacturing workflows in Australian prefabricated timber construction. Full article

Reducing embodied greenhouse gas emissions in the initial design phase is essential for attaining low-carbon buildings, as the highest potential for reduction exists prior to the finalization of construction decisions. While Building Information Modelling (BIM) and Life Cycle Assessment (LCA) have been progressively integrated for embodied carbon evaluation, current frameworks are predominantly deterministic, offer minimal uncertainty quantification, and seldom utilize machine-learning-assisted optimization to facilitate design decision-making. This paper presents an uncertainty-aware BIM–LCA methodology to solve these shortcomings, integrating automated quantity takeoff, probabilistic carbon assessment, and explainable machine-learning optimization. The proposed methodology integrates IFC-based BIM models, Bills of Quantities (BoQs), and regional life cycle inventory databases to conduct a cradle-to-grave embodied carbon assessment. Quantities produced from BIM were checked against BoQ data, and the uncertainty related to material quantities and emission factors was assessed by Monte Carlo simulation. A machine-learning surrogate model was created with 1200 design samples to facilitate swift optimization, and SHapley Additive exPlanations (SHAPs) were utilized to determine the most significant design factors. A mid-rise residential structure in Chongqing, China, encompassing a gross floor area of 9750.03 m², was used as a case study. The baseline Global Warming Potential (GWP) was calculated as 514.29 ± 30.09 kgCO₂e/m² (A1–A5), with product-stage emissions (A1–A3) accounting for roughly 89.28% of total embodied carbon, predominantly from concrete and steel. Enhanced BIM maturity lowered uncertainty by roughly 20%. Optimization resulted in a 38.13% decrease in embodied carbon, reducing GWP to 318.21 kgCO₂e/m². SHAP research identified the percentage of material reuse and concrete composition as the primary factors influencing carbon reduction. The suggested framework offers a clear and replicable decision-support mechanism for low-carbon building design that accounts for uncertainty. Full article

This paper examines how Small and Medium-sized Enterprises (SMEs) in the construction industry approach Building Information Modeling (BIM) adoption in a context marked by slow uptake and market fragmentation, with reflections on the Portuguese context. BIM is internationally recognized as a technology that can improve project coordination, productivity, and information management, but its level and patterns of use vary widely. Based on a structured exploratory literature review and an interpretive scoring framework, this paper identifies challenges and enabling factors associated with BIM adoption in SMEs. The findings suggest that BIM adoption should not be understood as a simple technological change; rather, it can be interpreted as a complex socio-technical process shaped by interdependence among technical, financial, organizational, and human dimensions. This study conceptualizes fragmentation in the construction industry as a reinforcing condition that may amplify barriers and help explain why many implementation approaches have limited effectiveness. Given this context, SME progression may require incremental, context-adapted approaches based on collaboration, information management, and capacity-building initiatives. This article contributes an exploratory conceptual framework for understanding BIM adoption in economically constrained and difficult-to-transform environments. It provides a basis for future empirical studies and SME-oriented strategies, including potential applications within the Portuguese construction sector. Full article