Search Results (107)

Building information models (BIMs) serve as a foundational tool for digital management of existing structures. Traditional methods suffer from low automation and heavy reliance on manual intervention. This paper proposes an automated method for structural component dimension recognition and BIM modeling based on 3D point cloud data. The proposed methodology follows a three-step workflow. First, the raw point cloud is semantically segmented using the PointNet++ deep learning network, and individual structural components are effectively isolated using the Fast Euclidean Clustering (FEC) algorithm. Second, the principal axis of each component is determined through Principal Component Analysis, and the Random Sample Consensus (RANSAC) algorithm is applied to fit the boundary lines of the projected cross-sections, enabling the automated extraction of geometric dimensions. Finally, an automated script maps the extracted geometric parameters to standard IFC entities to generate the BIM model. The experimental results demonstrate that the average dimensional error for beams and columns is within 3 mm, with the exception of specific occluded components. This study realizes the efficient transformation from point cloud data to BIM models through an automated workflow, providing reliable technical support for the digital reconstruction of existing buildings. Full article

This article focuses primarily on the current possibilities of using data and information from BIM models to estimate costs using identified methods and pricing systems for apartment buildings with different construction technologies. The authors analyse buildings with a built-up space of 3600–5300 m³, representing hundreds of projects currently available on the market. The applied methods include Pricing of Buildings Using a Spreadsheet Program, IFC-Supported Pricing Software, Pricing of Buildings in Design Software, and Pricing of Buildings Using a Design/Construction Library to compile cost estimates in the Czech URS, German Baupreislexikon, and British Spon’s Architects’ and Builders’ Price Book pricing systems. The usability of the BIM model with respect to the selected pricing system, construction technology, and methods ranges from 50% to 85%, with labour intensity ranging from 64 to 159 h. The key aspects for a wider application of BIM models include the completion of standardization at the level of graphic and non-graphic requirements related to the intended use of the data and information. The average cost per cubic metre of built-up space is EUR 469 in the Czech Republic, EUR 617 in Germany, and EUR 671 in Great Britain. This study brings new and distinctive insights compared to previous research by providing specific values for labour intensity and extractability, defining the limits of BIM use for cost estimation, and proposing recommendations to increase the applicability of the obtained data in practice. Full article

The integration of Building Information Modelling (BIM), blockchain technology, and smart contracts presents a significant opportunity to fundamentally reevaluate the administration of information and contracts in construction projects. This article introduces a distributed system that amalgamates BIM models, decentralized storage via IPFS, semantic oracles, and smart contracts to automate essential procedures such as versioning, design verification, and payment issuance contingent upon execution milestones. This proof of concept, built on a Proof-of-Authority blockchain using actual IFC models, demonstrates the technical viability of the method and evaluates its performance, constraints, and operational implications. The applications of SAL automation and design review demonstrate that integrating off-chain verification with on-chain documentation can reduce uncertainty, enhance accountability, and enable hitherto unattainable forms of contract automation. The suggested framework acknowledges the need for improved information standards and Oracle governance, demonstrating that integrating BIM and distributed technologies can significantly transform the digitalisation of the construction sector. Full article

Project control in cost estimation, time scheduling, and resource accounting remains challenging, particularly when using the open-source Industry Foundation Classes (IFCs) format. This study aims to define the state of the art in integrating these three domains. A systematic literature review was conducted, using a bibliometric analysis to map and interpret scientific knowledge and research trajectories, and an inductive analysis for a detailed examination of relevant studies. The analysis highlights a lack of clarity in applying the IFC standard across project control domains, as current practices often rely on non-standardized procedures, including incorrect use of classes or properties, creation of unneeded user-defined PropertySets and properties, or reliance on proprietary software. Integration of cost, time, and resource management remains limited, and proposed technological solutions generally require coding skills that typical professionals do not possess. Additional challenges include fragmented data across multiple databases, manual assignment of time, cost, and resource information, and limited collaboration, all of which are time-consuming and error-prone. There is a critical need for clearer guidelines on IFC usage to enable standardized procedures and facilitate the development of IFC-based tools. Automating these labor-intensive tasks could improve efficiency, reduce errors, and support broader adoption of integrated project control practices. Full article

In this study, a topological matching algorithm is introduced for semantic vertex detection to automate dimension generation in a building information modeling (BIM) environment based on the Industry Foundation Classes (IFC) standard. Conventional IFC-based quantity take-off (QTO) methods provide only standardized attributes, such as height, length, width, and area; therefore, user-defined custom dimensions—such as net opening sizes or parameter lengths—must be calculated manually. This study proposes a method for fully automating the dimensions required by users by automatically tagging and visualizing semantic vertices for geometrically identical IFC objects. These semantic vertices correspond to representative topological feature points (e.g., left–bottom–origin, left–top–front, left–bottom–back, and right–bottom–front). Based on these defined semantic vertices, the method automatically establishes vertex correspondence among objects to generate dimensions. The proposed workflow comprises four main stages: (1) geometry normalization of IFC objects, (2) semantic vertex definition, (3) automatic detection of semantic vertices, and (4) dimension generation and visualization. The experimental results demonstrate that the proposed approach successfully enables the computation of dimensions for geometrically identical objects, thereby significantly improving the efficiency of QTO processes. Full article

This paper discusses the evolution of convolutional (CNN) and recurrent (RNN) artificial neural networks in applications for Building Information Modeling (BIM). The paper outlines the milestones reached in the last two decades. The article organizes the current state of knowledge and technology in terms of three aspects: (1) computer visualization coupled with BIM models (detection, segmentation, and quality verification in images, videos, and point clouds), (2) sequence and time series modeling (prediction of costs, energy, work progress, risk), and (3) integration of deep learning results with the semantics and topology of Industry Foundation Class (IFC) models. The paper identifies the most used architectures, typical data pipelines (synthetic data from BIM models, transfer learning, mapping results to IFC elements) and practical limitations: lack of standardized benchmarks, high annotation costs, a domain gap between synthetic and real data, and discontinuous interoperability. We indicate directions for development: combining CNN/RNN with graph models and transformers for wider use of synthetic data and semi-/supervised learning, as well as explainability methods that increase trust in AECOO (Architecture, Engineering, Construction, Owners & Operators) processes. A practical case study presents a new application, Bimetria, which uses a hybrid CNN/OCR (Optical Character Recognition) solution to generate 3D models with estimates based on two-dimensional drawings. A deep review shows that although the importance of attention-based and graph-based architectures is growing, CNNs and RNNs remain an important part of the BIM process, especially in engineering tasks, where, in our experience and in the Bimetria case study, mature convolutional architectures offer a good balance between accuracy, stability and low latency. The paper also raises some fundamental questions to which we are still seeking answers. Thus, the article not only presents the innovative new Bimetria tool but also aims to stimulate discussion about the dynamic development of AI (Artificial Intelligence) in BIM. Full article

Despite regulatory advances, there continues to be a high accident rate on construction sites, especially on road projects, mainly due to the lack of organization of safety information. Although there is research demonstrating the benefits of the BIM methodology for improving occupational safety, its scope is still limited. This study addresses the integration of occupational health and safety in road projects using the BIM methodology, in line with ISO 19650-1, proposing a standardization framework based on ISO 7817-1:2024. The concept of Level of Information for Safety and Health (LOINSH) is introduced, structured into four categories (100, 200, 300, and 350), which allows risks to be managed progressively throughout the project’s life cycle. The framework defines graphical and alphanumeric requirements for BIM objects, establishing sets of parameters recognized by the open IFC format to ensure interoperability and traceability. It also proposes a system for assessing risks associated with activities and disciplines, facilitating preventive decisions from the design stage onwards. The results indicate that this standardization improves communication and collaboration between agents, reduces workplace accidents, and can be applied to other types of construction works. Full article

Purpose: The aim of this review is to evaluate the role of intraoperative flow cytometry (IFC) in tumor surgery. Methods: The Medline, Scopus, and Cochrane databases were searched up to 21 June 2025 to identify all available studies that met the inclusion criteria for final evaluation. To assess the risk of bias and applicability concerns, the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool was used. Results: A total of 22 studies involving 1511 patients with various tumor types were analyzed to assess the utility of IFC in the rapid diagnosis of tumors. The studies investigated IFC’s role in tumor grading, margin delineation, prognostic evaluation, and in differentiating neoplastic from benign lesions, as well as normal from cancerous tissues. In brain tumors, particularly gliomas and meningiomas, IFC demonstrated high diagnostic performance, with reported sensitivities ranging from 61% to 100% and specificities from 66% to 100%. Studies on non-brain tumors also showed high accuracy in distinguishing neoplastic from normal tissues, with sensitivities and specificities exceeding 85% in most cases. The most promising results were observed in brain tumor surgery, although its application in other tumor types continues to expand. Conclusions: IFC appears to be a valuable intraoperative tool in surgical oncology, providing rapid results within minutes and assisting in surgical and therapeutic decision-making. Nonetheless, studies remain limited, and further research is needed, particularly for non-brain tumors, to establish standardized cut-off values and enhance diagnostic reliability. Full article

This paper presents an implemented methodology to convert highly detailed building information models (BIMs) into geospatial 3D city models (Geos) at multiple levels of detail (LoDs). As BIM models contain highly detailed and complex geometries that differ significantly from city model standards, abstraction and conversion methods are required to generate usable outputs. Our study addresses this by developing a methodology that generates nine different LoDs from a single IFC input. These LoDs include both volumetric and surface-based abstractions for exterior and interior representations. The methodology involves voxelisation, filtering and simplification of surfaces, footprint derivation, storey abstraction, and interior geometry extraction. Together, these approaches allow flexible conversion tailored to specific applications, balancing accuracy, complexity, and computational efficiency. The methodology is implemented in a prototype tool named IfcEnvelopeExtractor. It automates IFC-to-CityGML/CityJSON conversion with minimal user input. The methodology was tested on a variety of models ranging from small houses to multistorey buildings. The evaluation covered geometric accuracy, semantic accuracy, and model complexity. Results show that non-volumetric abstractions and interior abstractions performed very well, producing robust and accurate results. However, the accuracy decreased for volumetric and complex abstractions, particularly at higher LoDs. Problems included missing or incorrectly trimmed surfaces, and modelling gaps and tolerance issues in the input IFC models. These limitations reveal that the quality of the input BIM models significantly affects the reliability of conversions. Overall, the methodology demonstrates that automated, flexible, and open-source solutions can effectively bridge the gap between BIM and geospatial domains, contributing to scalable GeoBIM integration in practice. Full article

The subject of this article is the information model of a building, the data of which can be used in the phase of operation and use. The aim of the article is to define the requirements for building information models for the purpose of data collection for spatial evidence. The article describes the method of sorting data according to the IFC standard developer for the international non-profit organization buildingSMART, or a classification system, and it describes the method of sorting the relevant data. Spatial evidence describes using the data from building information models. The conclusions of the article provide the information on how the users can collect the data from the information model and create spatial evidence in this case. Spatial evidence was selected because it is the one of the essential documents used by facility managers. Full article

In smart home projects, building data management at the design stage increasingly relies on digital-twin assets delivered via game engines. Without a clear governance workflow, however, these practices tend to generate non-standard building data on the consumption side, causing broken data chains and increasing construction and management risks. To address this problem, this study proposes a traceability-oriented governance workflow that strengthens IfcGUID compliance and automatically detects and converts inconsistent digital-twin assets into IFC-compliant, auditable data, thereby reducing data chain breakage and improving cross-system traceability in building data management. The workflow uses IfcGUID as a cross-system primary key and is evaluated in a virtual smart home project through a pre-test–repair–post-test experiment at the design stage. We examine four indicators of IfcGUID quality—completeness, validity, uniqueness, and stability—together with a bridge recognition rate that reflects game engine interoperability on the consumption side. The results show that all four IfcGUID indicators converge towards 1 after applying the workflow, and the bridge recognition rate approaches 100%, indicating that the risk of data chain breakage, measured on an IFC basis, is substantially reduced. Within existing toolchains, this workflow provides design teams, visualization teams, clients, and auditors with a low-cost and reproducible path for standardizing design-stage digital-twin assets and establishing a traceable, auditable baseline for cross-system interoperability and lifecycle building data management and data reuse. Full article

This study presents a Digital Twin–Mixed Reality (DT–MR) framework for the immersive and interactive supervision of automated container terminals (ACTs), addressing the fragmented data and limited situational awareness of conventional 2D monitoring systems. The framework employs a middleware-centric architecture that integrates heterogeneous subsystems—covering terminal operation, equipment control, and information management—through standardized industrial communication protocols. It ensures synchronized timestamps and delivers semantically aligned, low-latency data streams to a multi-scale Digital Twin developed in Unity. The twin applies level-of-detail modeling, spatial anchoring, and coordinate alignment (from Industry Foundation Classes (IFCs) to east–north–up (ENU) coordinates and Unity space) for accurate registration with physical assets, while a Microsoft HoloLens 2 device provides an intuitive Mixed Reality interface that combines gaze, gesture, and voice commands with built-in safety interlocks for secure human–machine interaction. Quantitative performance benchmarks—latency ≤100 ms, status refresh ≤1 s, and throughput ≥10,000 events/s—were met through targeted engineering and validated using representative scenarios of quay crane alignment and automated guided vehicle (AGV) rerouting, demonstrating improved anomaly detection, reduced decision latency, and enhanced operational resilience. The proposed DT–MR pipeline establishes a reproducible and extensible foundation for real-time, human-in-the-loop supervision across ports, airports, and other large-scale smart infrastructures. 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

To address the practical needs for data sharing and exchange in the bridge engineering domain, this study creatively fills the definitional gap of IFC entities for steel bridges. In response to the deficiencies arising from the absence of domain-layer entity information in the IFC standard architecture, an extension strategy is proposed that integrates new entity definitions with customized property sets to enrich and formalize the steel bridge domain. On this basis, a foundational data framework for steel bridge structures is established, encompassing extended definitions for spatial structural units, assemblies, components, and parts. The customized property sets further expand the entity attributes related to the design and fabrication stages, thereby developing an IFC-based manufacturing information model for steel bridges. Furthermore, a parametric BIM modeling approach for steel bridges is introduced on the 3DEXPERIENCE platform, employing IfcOpenShell to inject semantic information and export models in standard IFC format. The proposed IFC extension and modeling methodology is demonstrated through its application to the Chengdu Q7 North Pedestrian Bridge project, confirming its practical value in enhancing the completeness and transferability of steel bridge BIM model information from the design phase through to fabrication. Full article

Interoperability between Building Information Modeling (BIM) and Facility Management (FM) depends on open, vendor-neutral standards. Yet, operational uptake remains constrained by fragmented workflows, incompatible schemas, and non-standardized delivery. This critical review synthesizes OpenBIM pathways—within the buildingSMART ecosystem (Industry Foundation Classes (IFC), Construction–Operations Building information exchange (COBie), Information Delivery Specification (IDS) v1.0, buildingSMART Data Dictionary (bSDD)) and the Level of Information Need (ISO 7817-1:2024)—across technical, managerial, and strategic dimensions. We searched major databases and used guided snowballing to screen a core corpus. Technically, persistent semantic inconsistencies and limited real-time, bidirectional exchange remain; open standards enable machine-checkable deliverables and API-friendly serializations. Managerially, weak Organizational Information Requirements (OIR) → Asset Information Requirements (AIR) → Exchange Information Requirements (EIR) alignment and unclear acceptance criteria undermine FM readiness. Strategically, procurement and risk management should mitigate vendor lock-in. We highlight gaps in FM ontologies and BIM–IoT synchronization and outline an agenda for Digital Twins, automation, and verifiable FM data quality within OpenBIM ecosystems. Full article