Search Results (1,816)

The preservation of cultural heritage presents persistent challenges due to the heterogeneity of methodologies, data structures, and information requirements involved in heritage projects. While conventional Building Information Modeling (BIM) workflows commonly rely on the Level of Development (LOD), heritage contexts require flexible and requirement-driven approaches to manage both geometric and semantic information according to stakeholder needs. To address these challenges, this study adopts a design-oriented approach that investigates the integration of the Level of Information Need (LOIN) within an OpenBIM-based Historic Building Information Modeling (HBIM) framework. The proposed methodology combines a systematic literature review with a practical case study to develop and implement an interoperable workflow articulating HBIM, Level of Information Need (LOIN), Industry Foundation Classes (IFC), and Information Delivery Specification (IDS). Within this framework, LOIN governs the relevance and granularity of information, while IFC and IDS ensure interoperability, data exchange, and conformity checking. The methodology is applied to a Moroccan heritage case study focusing on the documentation and management of building pathologies, including cracks, humidity, capillary rise, and material degradation. The results demonstrate that the proposed approach overcomes the limitations of LOD by enabling requirement-driven information management, thereby improving pathology documentation and supporting informed decision-making for cultural heritage conservation. Full article

Digital management of modern railway bridges, a substantial part of high-speed railway networks, is often hindered by manual interpretation of construction drawings for Building Information Modeling (BIM). While individual technologies like optical character recognition (OCR) and neural networks are well-established, their generic application often fails on complex engineering documents. To address this, a domain-adaptive automatic recognition and semantic interpretation framework is proposed for railway bridge construction drawings. The novelty of this work lies in a specialized hybrid data fusion strategy that intelligently merges vector CAD file parsing with morphology-denoised OCR, resolving spatial and semantic conflicts. Furthermore, a back-propagation (BP) neural network is explicitly adapted to classify the extracted text into specific engineering categories, overcoming the challenges of dense layouts and overlapping symbols. Finally, the framework achieves end-to-end integration by transforming these semantic entities directly into structured, IFC-compatible BIM parameters. Evaluated on 250 real-world drawings, the framework achieved an average F1-score of 91.0% in semantic classification and improved processing efficiency by 6.5 times compared to manual methods. Moreover, 93.8% of the extracted entities achieved strict BIM parameter correctness, defined as seamless mapping to Revit IFC attributes without manual intervention. Full article

Building Information Modeling (BIM) has fundamentally changed the way interdisciplinary coordination works in construction projects; however, the theoretical mechanisms underlying open collaboration standards in this field remain insufficiently explored. This article fills this gap by presenting a systematic analysis of the BIM Collaboration Format (BCF) through the lens of reification and serialization, two fundamental concepts in information systems theory. Although the BCF format is widely used in the industry and implemented in major BIM tools for clash detection and issue tracking, the existing literature treats it primarily as an operational tool, overlooking the deeper information systems principles that govern its architecture. The analysis demonstrates that BCF achieves reification by transforming informal coordination knowledge—such as verbally communicated clashes, scattered email threads, and undocumented design decisions—into first-class objects (Topic, Comment, Viewpoint) equipped with unique identifiers, typed attributes, ownership, temporal metadata, and formalized inter-object relationships. Further analysis was conducted on BCF’s serialization mechanisms, including XML encoding for file exchange, JSON for RESTful API communication, and ZIP archiving as a distribution container, each of which was selected to balance human readability, schema validation, compression, and cross-platform portability. The complementarity of these two mechanisms was examined: reification determines what to preserve and in what structure, while serialization determines how to encode and in what format, which together enable interoperable, auditable, and automatable coordination workflows in heterogeneous software environments. The analysis was illustrated with a real-world BCF example from a major infrastructure project in Poland, demonstrating practical alignment between theoretical constructs and their implementation. The research results provide both a conceptual foundation for researchers working on openBIM standards and practical guidance for practitioners seeking to optimize issue management, the implementation of a Common Data Environment (CDE), and the specification of Exchange Information Requirements (EIR). The study contributes new knowledge in three areas: (1) To the best of the authors’ knowledge, it provides the first systematic theoretical analysis of BCF through the lens of reification and serialization, filling a gap between the format’s widespread practical use and its limited theoretical understanding. (2) It demonstrates how the formal criteria of reification (unique identity, typed attributes, ownership, temporal metadata, and inter-object relationships) map onto specific BCF entities, offering a transferable analytical framework for evaluating other openBIM standards. (3) It identifies the complementarity of reification and serialization as a design principle that can guide the development of future standards for digital twins and IoT-based facility management. Full article

Prefabricated steel structures have been increasingly adopted in modern construction due to their high efficiency, sustainability, and industrialized production. However, their construction quality and efficiency are often compromised by accumulated geometric deviations during fabrication, transportation, assembly, and welding, while traditional construction control and welding processes remain highly dependent on manual measurements and empirical operations. To address these challenges, this study proposes a digital construction framework for prefabricated steel structures, integrating high-precision three-dimensional (3D) laser scanning, Building Information Modeling (BIM), and intelligent welding technologies. First, high-precision 3D laser scanning is employed to capture the as-built geometric information of prefabricated steel components, generating dense point cloud data for construction-stage deviation detection and quantitative comparison with BIM-based design models. Based on deviation analysis, a digital construction control strategy is established to support real-time feedback, error compensation, and assembly adjustment. An engineering case study involving a complex prefabricated steel structure is conducted to validate the proposed framework. The results demonstrate that the integrated digital construction and intelligent welding approach significantly improves assembly accuracy, weld positioning precision, and construction efficiency, while reducing manual intervention and error accumulation. Overall, this study contributes to the body of knowledge by proposing a unified closed-loop digital construction paradigm that integrates geometric perception, deviation-driven decision-making, and intelligent welding execution, thereby bridging the gap between construction control and robotic fabrication in prefabricated steel structures. Full article

This research introduces a novel methodology that combines Building Information Modelling (BIM) and Economic Multi-Criteria Decision-Making (EMCDM) with Neural Networks to optimize hybrid renewable energy systems in small communities. Its core aim is to improve sustainability, technical performance, and financial vokiability through integrated modelling and decision-making. The approach is applied to a hydropower site, evaluating five Scenarios (IDs 1–5) under a Community and Industry model. Financial benchmarks include a 10% Minimum Required Return and a 7-year payback period. ID3—hydropower, solar, and wind—proves most effective, with ANPV of €10,905 (wet) and €4501 (dry), and ROI of 155%/64%. Its ROIA/MRA Index peaks at 539%, and Payback/N ratios remain within acceptable limits (55%/96%). LCOE stays stable in average conditions (0.042–0.046 €/kWh), rising in dry years (0.07–0.10 €/kWh). Profitability differences primarily stem from demand and curtailment, rather than production costs. The NARX neural network reliably models SS% values from renewable inputs with low error across scenarios. The integrated BIM–EMCDM framework ensures transparent, sustainable, and risk-balanced energy system decisions for long-term autonomy. Full article

Existing BIM (Building Information Modeling) validation mechanisms, namely geometric clash detection and attribute completeness checking of individual objects (MVD, IDS), do not cover a significant category of informational incompleteness: situations in which the properties of interdependent entities become fully defined only as a result of their mutual presence in the model. This article introduces the new concept of ontosaturation as a new mechanism of formal ontology that formalizes this phenomenon. Ontosaturation describes the relationship between existentially independent entities whose certain properties remain undetermined (unsaturated) in isolation and acquire values only after the attributes of related objects are taken into account. The article proposes a formal definition of ontosaturation and the supporting concepts needed to apply it in practice. These include the saturant (an entity that completes the properties of another), the saturation cluster (a group of mutually saturating entities), and the saturation index, a metric enabling a quantitative assessment of the relational completeness of a BIM model at the level of a single entity (s(e)) and the entire model (S(M)). The concept of a saturation profile was also introduced, complementary to the Level of Information Need (LOIN) in accordance with the ISO 19650 series of standards, defining minimum saturation thresholds for successive phases of the project lifecycle. The mechanism was demonstrated using the example of an installation penetration through a fire separation wall, modeled in Autodesk Revit 2025, showing that collision detection and attribute validation fail to detect four unsaturated properties critical to fire safety and structural integrity, which ontosaturation identifies. The proposed approach constitutes a third layer of BIM model validation, alongside the geometric and attribute layers, addressing the relational completeness of information between interdependent objects. Full article

Underground utilities form an essential part of urban infrastructure, yet their importance often becomes apparent only when service disruptions occur. Excavation activities for maintenance, relocation, or new construction carry considerable risks, including utility strikes, project delays, worker injuries, and even fatalities. These risks are largely driven by incomplete or inaccurate information about the location, depth, or material properties of buried utilities. To address this challenge, this study proposes a comprehensive Building Information Modeling (BIM)-based framework for managing underground utilities throughout their lifecycles. The framework is structured into five key stages: data acquisition, data processing, modeling, system application, and data updating. A highway project was used as a case study to validate the proposed approach. The study involved the integrated modeling and visualization of the highway corridor, underground gas pipelines, and overground high-voltage transmission pylons using Autodesk Civil 3D, InfraWorks, and Navisworks. The developed model and workflow were subsequently reviewed with the client department. Application of the framework to a 5 km highway corridor identified five utility-road conflict points (three subsurface gas pipeline intersections and two overground pylon encroachments) that were not detectable from existing 2D records. Expert review by the client department confirmed that the BIM-based visualization and 4D simulation improved construction planning clarity and supported proactive utility relocation decisions. By simplifying information workflows and enabling collaboration among stakeholders, the proposed framework demonstrates strong potential to improve excavation safety, enhance decision-making, and support the wider adoption of BIM for underground utility management. Full article

Building Information Modelling (BIM) has emerged as a transformative approach for improving efficiency, coordination, and sustainability in the construction industry; however, its adoption in developing regions remains limited. In the Kurdistan Region of Iraq (KRG), BIM implementation—particularly within the residential construction sector—remains at an early stage and lacks comprehensive empirical investigation. This study aims to assess stakeholders’ perspectives on current BIM practices, identify key adoption barriers, and develop a context-specific strategic framework to support BIM implementation. A mixed-method research design was employed, incorporating literature review, expert validation through semi-structured interviews, and a structured questionnaire survey. A total of 319 valid responses were analyzed using descriptive statistics, Relative Importance Index (RII), Cronbach’s alpha for reliability, Spearman’s rank correlation, independent samples t-tests, and one-way ANOVA. In addition to ranking barriers, an inter-barrier correlation analysis was conducted to examine the relationships, clustering patterns, and hierarchical structure of BIM adoption challenges. The results indicate that while BIM awareness is moderately established among stakeholders, its practical application remains limited, particularly beyond the design phase. The most critical barriers include lack of training and expertise, absence of regulatory frameworks and standards, insufficient government support, and financial constraints. The correlation analysis reveals that these barriers are interdependent, with policy and institutional deficiencies acting as root drivers influencing technical, financial, and awareness-related challenges. Based on these findings, the study proposes a four pillar conceptual strategic framework encompassing human capital development, regulatory and standardization enablement, awareness and demand generation, and organizational and collaborative enhancement. The framework is explicitly derived from empirical results, linking barrier clusters to prioritized strategies, thereby enhancing its practical applicability. This study contributes to the existing literature by providing one of the first multi-province empirical assessments of BIM adoption in the KRG residential sector, integrating statistical validation with strategic development, and offering transferable insights for other developing regions at a similar stage of BIM adoption. Full article

Rapid urbanization and the growth of data-driven planning have increased the need for tools that support integrated, transparent, and accountable urban governance. While Building Information Modeling (BIM) is well established in project delivery, its potential role in city-scale governance remains underexplored. This study conducts a structured qualitative evidence synthesis informed by PRISMA reporting principles and comparative case analysis to investigate how BIM, in combination with GIS, IoT, and AI, intersects with emerging digital governance practices. Through a synthesis of peer-reviewed research and documented case studies, the review evaluates how BIM supports data integration, interoperability, decision-making, regulatory compliance, collaborative governance, and sustainability. The findings suggest that BIM functions as a governance-support infrastructure when embedded within coordinated institutional frameworks, standardized data environments, and interoperable digital ecosystems. Based on these insights, the paper proposes a conceptual framework that organizes BIM governance into technical, institutional, social, and ethical–regulatory dimensions. The review suggests that BIM’s governance potential depends on institutional alignment, regulatory clarity, and sustained organizational capacity, rather than technological capability alone. Full article

Building Information Modeling (BIM) supports information integration and coordination across the construction lifecycle, but benefits depend on collaboration that is shaped by the selected project delivery method (PDM). BIM-PDM evidence is difficult to consolidate due to heterogeneous terminology and fragmented, context-specific studies. This scoping review maps which PDMs are addressed in the BIM-related literature and how adequacy is framed. Following PRISMA-ScR, Web of Science and Scopus were searched and 71 studies met the eligibility criteria. Publications increased markedly after 2018 and were geographically concentrated, with the largest shares associated with author affiliations in China, the United Kingdom, Australia, Canada, Malaysia, and the United States. Integrated Project Delivery (IPD) was the most frequently examined (46 studies), followed by Design–Bid–Build (DBB) (29), Design–Build (DB) (29), Public–Private Partnership (PPP) (17), and Engineering, Procurement, and Construction (EPC) (14), while Alliancing, Lean-oriented delivery approaches, and Construction Management were comparatively underrepresented. A temporal analysis indicates a recent shift toward collaborative delivery methods in BIM research. Case-based studies are predominantly situated in public sector projects, with DBB, DB, EPC, and IPD examined across both infrastructure and building contexts, while PPP is limited to infrastructure. The literature is largely focused on design and construction phases, with limited attention to early project stages and operation and maintenance. Results indicate both traditional and relationship-based PDMs are studied in the existing literature, with research framing PDMs that allow for early contractor involvement as most compatible with BIM. Moreover, IPD, DB, and EPC show the best alignment compared to most used traditional DBB methods primarily due to the early involvement of the contractor in the project. EPC and DB achieve this through the allocation of responsibility to the contractor, whereas IPD relies on the early engagement of key participants and the systematic alignment of their objectives. Collaborative and relationship-based approaches are consistently presented as the most suitable for BIM, while DBB tends to constrain BIM benefits because of its fragmented nature. This study contributes by providing a systematic synthesis of BIM-PDM relationships in the scientific literature, identifying the key mechanisms underlying the suitability of different delivery methods for BIM implementation, and offering recommendations for future research based on the identified gaps. Full article

The integration of Building Information Modeling [BIM] and Digital Twins [DT] has emerged as a central driver of digital transformation in the architecture, engineering, and construction sector. Yet, its systemic impact remains constrained by conceptual fragmentation and uneven institutional adoption. This study synthesizes contemporary BIM–DT scalability and each to identify dominant technological and application dimensions, examine the governance conditions shaping scalability, and develop an analytical framework that advances understanding beyond technology-centered syntheses. A two-stage analytical design was employed, combining bibliometric keyword co-occurrence analysis of 1295 Scopus-indexed records with systematic qualitative synthesis of 56 peer-reviewed journal articles published between 2020 and 2025, following PRISMA guidelines. Six interrelated analytical dimensions characterize the current BIM–DT research landscape: BIM–DT integration advancements and applications; interoperability and visualization; safety enhancement; energy efficiency; data-driven decision making; and stakeholder collaboration. Across these dimensions, a persistent misalignment emerges between technological capability and organizational readiness, with deficiencies in standards, governance, and sociotechnical coordination constituting the principal barriers to large-scale deployment. The findings reframe BIM–DT convergence not as a discrete technological upgrade but as the emergence of a coordinated socio-technical information ecosystem spanning the full building lifecycle. By foregrounding governance conditions, data stewardship, and institutional coordination, this study extends understanding of how digital twins expand BIM from design coordination to operational governance and establishes a foundation for more systematic implementation of intelligent, resilient, and sustainable built-environment systems. Full article

Modular integrated construction (MiC) is an innovative construction method that shifts on-site activities to a controlled factory environment, thereby offering sustainability benefits. However, current carbon management relies on labor-intensive manual data collection, causing delayed and inaccurate carbon accounting that increases greenwashing risks. Existing approaches lack real-time, automated, and trustworthy carbon tracking capabilities across fragmented supply chains. This study develops and validates the Blockchain-enabled IoT-BIM Platform (BIBP), which combines Internet of Things (IoT), Building Information Modeling (BIM), and blockchain for real-time carbon monitoring. IoT sensors automate data capture from construction equipment and BIM provides spatial visualization of carbon at the module and building levels. A Hyperledger Fabric blockchain ensures the authenticity, immutability, and traceability of carbon records. Validated on a 15-story MiC project in Hong Kong, BIBP established a cradle-to-end-of-construction baseline of 949.84 kgCO_2e/m², identifying steel and concrete as the primary hotspots (80% of material emissions). Real-time analytics demonstrated that combining high-volume ground granulated blast furnace slag (GGBS) concrete substitution, new energy sea–land multimodal transport, and 10% steel waste reduction achieves over 20% carbon savings. Furthermore, the BIBP automated data acquisition and calculation, improving assessment efficiency by 92.4%. The platform demonstrates the potential to transform carbon management from a static, retrospective evaluation into a proactive, data-driven monitoring process, equipping stakeholders with a tool to dynamically track emissions and make timely interventions toward carbon reduction targets. Full article

The growing reliance on virgin resources in construction, alongside accelerated urban development and the significant volumes of waste generated at the end-of-life phase of buildings, has intensified environmental impacts across the built environment. These challenges highlight the urgent need to transition towards a circular economy (CE) in the construction sector. At the same time, the sector’s ongoing digital transformation presents opportunities to enhance stakeholder collaboration and improve construction and demolition waste management (CDWM) practices. This paper aims to develop a conceptual framework for a Digital Information Management System (DIMS) to support CE implementation in construction through improved CDWM. Following the Design Science Research methodology, this paper addresses the first two stages: problem identification and solution proposition. A questionnaire survey with industry experts was conducted to validate the problem areas identified in the literature and assess the applicability of the proposed conceptual framework. The findings confirm critical gaps in CDWM, including limited stakeholder collaboration, fragmented processes, and the absence of lifecycle-spanning information systems, and validate the proposed conceptual framework solution, particularly the integration of BIM and IoT to support material and product flow tracking throughout the project lifecycle, supported by clearly defined stakeholder roles and engagements. However, respondents expressed reservations regarding Blockchain due to concerns about energy consumption and long-term data storage. Overall, the validated conceptual framework for DIMS provides a robust foundation for future studies, to focus on co-creating and developing a detailed conceptual model for DIMS for future real-world implementation. Full article

The ongoing digitalization of building operation processes creates new opportunities to improve maintenance and renovation decision-making. Despite the increasing use of BIM, renovation decisions in residential buildings are still often based on fragmented data, heterogeneous documentation, and subjective expert assessments. This challenge is particularly relevant for large-panel housing in Central and Eastern Europe, where aging building stock requires systematic long-term modernization strategies. This paper presents a Renovation Decision Support System (RDSS) integrating a simplified BIM model, technical documentation, diagnostic data, and machine learning methods to support renovation planning. The system consists of five modules: the Building Information Model Module (BIMM), Geometric and Technical Documentation Module (GTDM), Building Condition Assessment Module (BCAM), Building Performance and Condition Prediction Module (BPCM), and Renovation Decision Optimization Module (RDOM). Data exchange is managed through a Common Data Environment (CDE). The system combines multi-criteria building condition assessment with fuzzy inference to determine renovation urgency and long-term optimization using Mixed-Integer Linear Programming (MILP). Budget constraints, activity sequences, time horizons, and user preferences are considered to generate alternative renovation scenarios. The proposed approach supports sustainable management of existing buildings, improves decision transparency, and enables data-driven renovation planning consistent with life-cycle management principles. Full article

Over the past decade, Building Information Modelling (BIM) has become increasingly adopted across the Architecture, Engineering, Construction, and Operation (AECO) industry. As its use in practice has expanded, BIM has also received growing scholarly attention. Existing research has largely concentrated on specific applications of BIM, such as construction management, sustainable building design, infrastructure development, and facility management. However, comparatively limited attention has been given to examining BIM implementation from a global perspective. This study addresses this gap by applying a scientometric approach to analyse global BIM implementation research published between 2004 and 2023. The analysis is conducted using co-authorship, co-word, and co-citation analysis to map the structure and development of the research field. A total of 1349 published articles were obtained from the Scopus database for the analysis. The study identifies the most productive and influential contributors to BIM implementation research, including leading researchers, research institutions, countries, subject areas, and academic journals. In addition, the analysis highlights several key thematic domains within global BIM research. These include topics related to Industry Foundation Classes (IFC), Internet of Things (IoT), Geographic Information Systems (GIS), Historic Building Information Modelling (HBIM), and Digital Twin technologies, which appear as prominent keywords within the BIM implementation literature. Beyond mapping these trends, this paper integrates dispersed scientometric evidence into a coherent global perspective, revealing how BIM implementation research has evolved, matured, and diversified across regions and disciplines. It also establishes a structured knowledge base that can serve as a benchmark for future comparative studies, performance assessments, and policy development initiatives in the digital construction domain. These findings provide valuable insights for researchers, practitioners, and policymakers by illustrating landscape of BIM-related research and highlighting potential directions for future investigation. Full article