Industry Foundation Classes Models Research Articles

Integration of Industry Foundation Classes and Ontology: Data, Applications, Modes, Challenges, and Opportunities

Industry Foundation Classes (IFCs), as the most recognized data schema for Building Information Modeling (BIM), are increasingly combined with ontology to facilitate data interoperability across the whole lifecycle in the Architecture, Engineering, Construction, and Facility Management (AEC/FM). This paper conducts a bibliometric analysis of 122 papers from the perspective of data, model, and application to summarize the modes of IFC and ontology integration (IFCOI). This paper first analyzes the data and models of the integration from IFC data formats and ontology development models to the IfcOWL data model. Next, the application status is summed up from objective and phase dimensions, and four frequent applications with maturity are identified. Based on the aforementioned multi-dimensional analysis, three integration modes are summarized, taking into account various data interoperability requirements. Accordingly, ontology behaves as the representation of domain knowledge, an enrichment tool for IFC model semantics, and a linkage between IFC data and other heterogeneous data. Finally, this paper points out the challenges and opportunities for IFCOI in the data, domain ontology, and integration process and proposes a building lifecycle management model based on IFCOI.

An ontology‐based rule mapping approach for integrating IFC and CityGML

AbstractBuilding information modeling (BIM) and geographic information system (GIS) are often integrated to achieve more refined urban management. Industry Foundation Classes (IFC) and City Geography Markup Language (CityGML) are widely used standards in BIM and GIS. The main problem of the transformation of these two standards lies in the gap between them in geometry and semantics. This article introduces an ontology‐based rule mapping approach, achieving the transformation from IFC to CityGML through coordinate system conversion, geometric expression conversion, and semantic mapping. For semantic mapping, we have designed and established rules, enabling the effective mapping of the IFC model to the CityGML level of detail 0 (LOD0) to LOD4 model based on entities, appearance properties and building properties. To fully demonstrate the entire process, we give a detailed elaboration of the conversion of several IFC models.

BIM in construction waste management: A conceptual model based on the industry foundation classes standard

Building Information Modeling (BIM) represents an innovation in the architecture, engineering, and construction (AEC) industry. In the environmental context, the management of buildings through BIM contributes to preserving resources and promoting more sustainable environments. This research explores the application of BIM in construction and demolition waste (CDW) management and the sustainability of buildings. The method consisted of applying Design Science Research (DSR) to develop a conceptual information model based on the Industry Foundation Classes (IFC) to meet CDW indicators and to assist in the CDW management activity. The conceptual model presented a perspective on application in CDW management and emphasized the importance of mapping information exchanges in BIM to optimize activities in civil construction. However, the results depend directly on the information available in the IFC model. The proposed conceptual model presents the potential to automate waste management with the flexibility of applying it to different phases of the construction life cycle. The results of CDW management can contribute to other types of sustainability analyses.

Integrating as-built BIM model from point cloud data in construction projects

PurposeAs laser scanning technology becomes readily available and affordable, there is an increasing demand of using point cloud data collected from a laser scanner to create as-built building information modeling (BIM) models for quality assessment, schedule control and energy performance within construction projects. To enhance the as-built modeling efficiency, this study explores an integrated system, called Auto-Scan-To-BIM (ASTB), with an aim to automatically generate a complete Industry Foundation Classes (IFC) model consisted of the 3D building elements for the given building based on its point cloud without requiring additional modeling tools.Design/methodology/approachASTB has been developed with three function modules. Taking the scanned point data as input, Module 1 is built on the basis of the widely used region segmentation methodology and expanded with enhanced plane boundary line detection methods and corner recalibration algorithms. Then, Module 2 is developed with a domain knowledge-based heuristic method to analyze the features of the recognized planes, to associate them with corresponding building elements and to create BIM models. Based on the spatial relationships between these building elements, Module 3 generates a complete IFC model for the entire project compatible with any BIM software.FindingsA case study validated the ASTB with an application with five common types of building elements (e.g. wall, floor, ceiling, window and door).Originality/valueFirst, an integrated system, ASTB, is developed to generate a BIM model from scanned point cloud data without using additional modeling tools. Second, an enhanced plane boundary line detection method and a corner recalibration algorithm are developed in ASTB with high accuracy in obtaining the true surface planes. At last, the research contributes to develop a module, which can automatically convert the identified building elements into an IFC format based on the geometry and spatial relationships of each plan.

BIM Search Engine: Effects of Object Relationships and Information Standards

As Building Information Modeling (BIM) models are getting bigger, with more information linked to geometrical 3D models, a dedicated BIM search engine is important. A BIM search engine was developed to examine the value of exploiting a 3D object’s topological relationships to other 3D objects when assessing that object’s relevance to a query. The impacts of two information standards, the Industry Foundation Classes (IFC) and Uniclass-2015, on information retrieval (IR) performance were also measured. The 3DIR Autodesk Revit toolset was used on a structural model of a 16-story building from an industry partner. The retrieval performance measures of Precision and Recall did not clearly highlight the benefit, although the increased relevance values of those objects deemed by experts to be relevant demonstrates the promise of such contextual measures. The effect of shifting from the native Revit file format to various standards was tested: IR performance was poor with the Uniclass-2015 dataset and was comparable to the Revit native model with the IFC model. Although not shown conclusively to improve retrieval performance, the contextual relevance measures presented in this paper are promising and constitute a significant original contribution. Future research is needed to fine-tune these measures and fully realize their potential.

An Automated Space-Based Graph Generation Framework for Building Energy Consumption Estimation

The 3D information in Building Information Modeling (BIM) has received significant interest for smart city applications. Recently, employing Industry Foundation Classes (IFC) for BIM in data-driven methods for Building Energy Consumption Estimation (BECE) has gained momentum because of the enriched geometric and semantic information. However, despite extensive studies on applying the IFC data in BECE analysis, employing the full potential of the BIM remains poor due to its complex data model and incompatibility with data-driven algorithms. This paper proposes a framework to extract accurate semantic, geometry, and topology information from the room-level (space) IFC schema by introducing new geo-computation algorithms to deal with these challenges. Additionally, we define a new topological weighted relationship between spaces in different stories by combining common geometry area with energy resistance value. Eventually, the proposed weighted space-based graph will be constructed to decrease the original complexity of the IFC model, and it is compatible with graph-based machine learning algorithms. The results are promising, with more than 90% accuracy in extracting the geometry information for the convex and non-convex polyhedron rooms and 100% accuracy in detecting vertical and horizontal adjacent rooms. This study confirms the proposed approach’s efficiency, accuracy, and feasibility for space-based BECE analysis.

How to exploit BIM/IFC for 3D registration of ownership rights in multi-storey buildings: an evidence from Turkey

The condominium rights, which is a special ownership type that can only exist in the buildings that have an occupancy permit, are needed to be examined and depicted as three-dimensional (3D) in order to prevent misinterpretations and disputes regarding Rights, Restrictions, and Responsibilities (RRRs). This paper, therefore, aims to provide the model that extends the Industry Foundation Classes (IFC) schema by referencing Land Administration Domain Model (LADM) in the sense of reusing the Building Information Modeling (BIM)/IFC model of the building for 3D registration of condominium rights in Turkey. The results of the study show that there is a solid potential to benefit from BIM/IFC model in order for both 3D representation of the ownership rights in the multi-storey buildings and obtaining the semantics of the condominiums in terms of wide ranges of attributes such as area, volume, land share, and RRRs.

Digital twin-enabled built environment sensing and monitoring through semantic enrichment of BIM with SensorML

Effective environmental condition monitoring provides constant surveillance of the built environment and reveals deteriorations that could impact the daily operation of facilities, especially amid COVID situations. However, the current Industry Foundation Classes (IFC) data schema for Building Information Modelling (BIM) provided limited support to represent full semantics related to environmental sensing and monitoring. How to semantically enrich the IFC schema with enhanced data description capability for informed decision-making in smart facilities management (FM) amid COVID situations remains an open question. This paper develops a semi-automatic extension and integration of IFC data schema with Sensor Model Language (SensorML) specification in order to support automated built environment sensing and monitoring. Referring to SensorML, an extended IFC model view definition for a comprehensive description of required sensor metadata and sensing entities is presented. An Internet of Things (IoT) sensor network is then established to realise continuous data collection from a variety of wireless sensing devices. The spatial-temporal data captured by the IoT sensor network are extracted by a regular expression-based data distillation algorithm and integrated with the digital twin, in which spatial interpolation algorithms further analyse, compute, and visualise the state of the environment. The proposed method is demonstrated via an experimental study which supports real-time environmental monitoring and delivers more actionable insights to facility managers to sustain the daily operation of buildings. This study contributes new methods and models to semantically enrich the digital twin from the data perspective for environmental condition monitoring during the pandemic time which fosters the development of holistic building facility management.

IFC BIM Model Enrichment with Space Function Information Using Graph Neural Networks

The definition of room functions in Building Information Modeling (BIM) using IfcSpace entities is an important quality requirement that is often not fulfilled. This paper presents a three-step method for enriching open BIM representations based on Industry Foundation Classes (IFC) with room function information (e.g., kitchen, living room, foyer). In the first step, the geometric algorithm for detecting and defining IfcSpace entities and injecting them into IFC models is presented. After deriving the IfcSpaces, a geometric method for calculating the graph of connections between spaces based on accessibility is described; this information is not explicitly stored in IFC models. In the final step, a graph convolution-based neural network using the accessibility graph to classify the IfcSpace entities is described. Local node features are automatically extracted from the geometry and neighboring elements. With the help of a Graph Convolutional Network (GCN), the connection and spatial context information is utilized by the neural network for the classification decision, in addition to the local features of the spaces which are more commonly used. To evaluate the classification accuracy, the model was tested on a set of residential building IFC models. A weighted version of the common GCN was implemented and tested, resulting in a slight improvement in the classification accuracy.

Towards Automated Structural Stability Design of Buildings—A BIM-Based Solution

Building information modelling (BIM) is a revolution in the architectural, engineering, and construction (AEC) industry. In the AEC industry, several interesting innovations are being introduced every day. Most of the code compliance work, which is time-consuming and quite multifaceted, is now performed manually. The number of unwanted errors is increasing, and any suspension of the project is led by the structural code-checking system, and is a tiresome process. Subsequently, the BIM-based model is presented to automate the structural stability design of buildings. The Industry Foundation Classes (IFC) specification is introduced in this work, and is used to automate the building design processes to achieve design correctness and efficiency. The IFC-based interoperability framework is presented to automate the design of structural elements of RC buildings. Consequently, a deep multi-perception-based generalized adaptive framework (DMPBGAF) is presented for the automated code compliance checking process. The concepts and relationships in the building code were automatically matched to their equivalent concepts. A building code was checked against the Indian seismic code IS 13920, and when shear wall data were presented in this IFC file, it exchanged the data with the custom engine. It is possible to eliminate the unwanted issues based on the automated code compliance system with BIM. This goal can be accomplished by using a coding rule-based engine to compile the BIM model and store the design code of the specific country with its clauses. After generating the Python file to code all of the prepared checks, the python file in the form of functions was obtained from the IfcOpenShell library. Finally, a rule engine was developed for interpretation of the checks; the three model IFC files were tested on this, and it gave satisfactory results. The FreeCAD software was employed in this research for the IFC-based BIM model to automate the design. The shear wall data were presented in the first IFC model; all of the code checks were passed based on this modelled design, and when given to the rule engine, it gave a 100% compliance report. Insufficiently reinforced shear wall data contained in the other two IFC files were purposely created to fail some of the code checks. This method significantly reduces the time by eliminating the duplication of efforts. From the viewpoint of accuracy and reliability, the proposed method is more accurate and results in enhanced reliability as compared to manual design methods.

Development of Open-Assistant Environment for Integrated Operation of 3D Bridge Model and Engineering Document Information

This study proposes a method for assistant environments to integrate 3D bridge model information and engineering document fragments. The engineering document content varies depending on the process. Therefore, we accept a loose coupling concept to support the independence of each information set instead of using a specific data model for effective integration. The engineering document is translated into an Extensible Markup Language (XML)-based structured format based on the explicit and apparent semantic structure of the document. An extended industry foundation classes (IFC) schema is proposed to manage the bridge information model, as well as document fragments. An information document (iMapDoc) is proposed to manage interim data to connect a 3D digital model, an IFC model, and engineering document fragments. Document fragments on a specific component in the 3D bridge model are retrieved to validate the developed integrated assistant module.

PARAMETRIC MODELLING APPROACH TO RECONSTRUCTING ARCHITECTURAL INDOOR SPACES FROM POINT CLOUDS

Abstract. In this paper, some outcomes of a research project which aims to introduce automation to speed up modelling of architectural spaces based on point clouds are presented. The main objective of the research is to replace some manual parametric modelling steps with automatic processes to obtain editable models in BIM-ready software and not to generate non-parametric IFC (Industry Foundation Classes) models. An approach of automation using visual programming for interior wall modelling based on point clouds is presented. The pipeline and the different concepts represented in this paper are applicable using different programming languages but here the use of Rhinoceros as a modelling software and its open-source visual programming extension "Grasshopper" is intentional as it is in common use for parametric modelling and generative design in architectural practice. In this research, it is assumed that there is a predominance of three mutually orthogonal directions of the walls in the interior spaces to be analysed, which is the case of most indoor spaces.

Building Information Modelling for performance-based Fire Safety Engineering analysis – A strategy for data sharing

The Hackitt Report into the tragic loss of 72 lives in the Grenfell Tower fire, identified failures and poor practices associated with the UK construction industry. To address these failures the report makes several recommendations, including the development of a “golden thread of information” to be embedded throughout the entire building lifecycle enabling the recording and preservation of information. This is to be achieved through Building Information Modelling (BIM). However, to create a “golden thread of information” in BIM from the Fire Safety Engineering (FSE) perspective particularly for the performance-based approach, many significant challenges and limitations must be resolved. These challenges include the fact that no FSE specific information exchange is available in BIM and that the results produced by fire and evacuation modelling tools are not explicitly captured in the BIM Industry Foundation Classes (IFC) Model. Of the FSE tools that support BIM, this is mainly limited to geometry extraction from an IFC file. In this paper, a practical conceptual strategy to pave the way to resolve these problems is proposed. A number of developments by the authors are discussed, forming part of an international collaboration project proposal administered by buildingSMART to enhance the IFC Model from the FSE perspective. Additionally, to evaluate and demonstrate the benefits of two-way data flow between BIM and FSE tools, a prototype system together with a preliminary FSE based analysis database have been developed. The work presented in this paper, provides a practical road map for creating a ‘golden thread of information’ in BIM for performance-based FSE analysis.

BIM-BVBS integration with openBIM standards for automatic prefabrication of steel reinforcement

Processing steel reinforcement is an on-site activity that includes cutting and bending, which are time-consuming and uneconomical. When moving toward the construction automation, off-site prefabrication is important with the aid of Building Information Modeling (BIM) and Industry Foundation Classes (IFC) which are utilized as a collaborative approach to facilitate the fabrication workflow and data interoperability. This paper presents the integration of BIM and steel fabrication machine codes (BVBS) with openBIM standards to interoperate the computerized design and prefabrication automation of steel reinforcement. The integration begins with the reference of Information Delivery Manual (IDM) which involves the identification of information requirement in the process map for identifying the necessary data exchange within the prefabrication process. Definition of IFC model views is conducted to ensure that the exchange of data meets the end user's needs and is implementable for software applications. Next, the process information model of steel reinforcement fabrication is established by connecting the IFC entities with relationships among the specific tasks. A new approach is developed to extend the IFC data schema with prefab-related entities. The proposed BIM-BVBS integration is demonstrated utilizing IFC viewers and visual programming tools (Dynamo) in illustrative examples, the results of which reveal that prefab-related entities and attributes in IFC-based BIM models can be extracted efficiently to cater to the BVBS data transformation toward automatic prefabrication.

An Inspection of IFC Models from Practice

Industry Foundation Classes (IFC) is a complete, wide and complex open standard data model to represent Building Information Models. Big efforts are being made by the standardization organization buildingSMART, to develop and maintain this standard in collaboration with researchers, companies and institutions. However, when trying to use IFC models from practice for automatic analysis, some issues emerge, as a consequence of a misalignment between what is prescribed by, or available in, the standard with the data sets that are produced in practice. In this study, a sample of models produced by practitioners for aims different from their explicit use within automatic processing tools is inspected and analyzed. The aim is to find common patterns in data set from practice and their possible discrepancies with the standard, in order to find ways to address such discrepancies in a next step. In particular, it is noticeable that the overall quality of the models requires specific additional care by the modellers before relying on them for automatic analysis, and a high level of variability is present concerning the storage of some relevant information (such as georeferencing).

Simulation method for indoor airflow based on the Industry Foundation Classes model

Indoor airflow is an important factor affecting indoor thermal comfort and human health; it is also an important consideration for architectural design, ideal living environments, and green building fields. Currently, most building models required for indoor airflow simulation have been manually created by researchers, which is inefficient and error-prone in modeling. To overcome this problem, this study examines the similarities and differences between the general standard data model Industry Foundation Class (IFC) in the BIM (Building Information Model) and the spatial grid required for indoor airflow simulation and proposes a conversion method from an IFC model to spatial grid. This method uses the rich semantic, geometric, and relational information in the IFC model to automatically extract building interior space, divide numerical calculation grid, and map semantic attribute information to the spatial grid. On this basis, an integrated simulation framework is constructed with OpenFOAM to simulate the airflow movement of the indoor space of the building. The simulation results show that the method used in this study can automatically construct the spatial grid using existing IFC models without re-modeling, which provides important support for indoor airflow modeling. In addition, the integrated simulation framework connects model construction, simulation analysis, and other steps through tool chain. This process simplifies the simulation operation, provides convenience for indoor airflow simulation, is conducive to the wide use of indoor airflow simulation in architectural design and architectural design optimization, and also provides reference for related numerical simulation research and digital city modeling.

Automatic classification of wall and door BIM element subtypes using 3D geometric deep neural networks

With the growing adoption of Building Information Modeling (BIM), specialized applications have been developed to perform domain-specific analyses. These applications need tailored information with respect to a BIM model element’s attributes and relationships. In particular, architectural elements need further qualification concerning their geometric and functional ‘subtypes’ to support exact simulations and compliance checks. BIM and its underlying data schema, the Industry Foundation Classes (IFC), provide a rich representation with which to exchange semantic entity and relationship data. However, subtypes for individual elements are not represented by default and often require manual designation, leaving it vulnerable to errors and omissions. Existing research to enrich the semantics of IFC model entities employed domain-specific rule sets that scrutinize their legitimacy and modify them, if and when necessary. However, such an approach is limited in their scalability and comprehensibility. This study explored the use of 3D geometric deep neural networks originating from computer vision research. Specifically, Multi-view CNN(MVCNN) and PointNet were investigated to determine their applicability in extracting unique features of door (IfcDoor) and wall (IfcWall) element subtypes, and in turn be leveraged to automate subtype classifications. Test results indicated MVCNN as having the best prediction performance, while PointNet’s accuracy was hampered by resolution loss due to selective use of point cloud data. The research confirmed deep neural networks as a viable solution to distinguishing BIM element subtypes, the critical factor being their ability to detect subtle differences in local geometries.

Tools for BIM-GIS Integration (IFC Georeferencing and Conversions): Results from the GeoBIM Benchmark 2019

The integration of 3D city models with Building Information Models (BIM), coined as GeoBIM, facilitates improved data support to several applications, e.g., 3D map updates, building permits issuing, detailed city analysis, infrastructure design, context-based building design, to name a few. To solve the integration, several issues need to be tackled and solved, i.e., harmonization of features, interoperability, format conversions, integration of procedures. The GeoBIM benchmark 2019, funded by ISPRS and EuroSDR, evaluated the state of implementation of tools addressing some of those issues. In particular, in the part of the benchmark described in this paper, the application of georeferencing to Industry Foundation Classes (IFC) models and making consistent conversions between 3D city models and BIM are investigated, considering the OGC CityGML and buildingSMART IFC as reference standards. In the benchmark, sample datasets in the two reference standards were provided. External volunteers were asked to describe and test georeferencing procedures for IFC models and conversion tools between CityGML and IFC. From the analysis of the delivered answers and processed datasets, it was possible to notice that while there are tools and procedures available to support georeferencing and data conversion, comprehensive definition of the requirements, clear rules to perform such two tasks, as well as solid technological solutions implementing them, are still lacking in functionalities. Those specific issues can be a sensible starting point for planning the next GeoBIM integration agendas.

Extended IFC-based strong form meshfree collocation analysis of a bridge structure

Building Information Modeling (BIM)-based finite element analysis is challenging owing to inefficiencies, such as the manual meshing/remeshing process performed by experts and excessive analysis-related information due to different input points and result nodes. To overcome these limitations, we proposed a new analysis framework that integrates the meshfree analysis method into the Industry Foundation Classes (IFC)-based bridge model. We added the IFC entities to manage information for the bridge structures and meshfree analysis based on the IFC extension concept. We developed modules for generating the bridge model based on the proposed schema. The data required for meshfree analysis were presented through the extraction and conversion process from the IFC model. Finally, the proposed framework was applied to the stress analysis of the bridge structure to demonstrate the efficiency of the method. As a result, we confirmed the possibility of seamless information exchange and interoperability between the architectural and structural analysis models.

Automatically Processing IFC Clipping Representation for BIM and GIS Integration at the Process Level

The integration of building information modeling (BIM) and geographic information system (GIS) is attracting more attention than ever due to its potential benefits for both the architecture, engineering, and construction (AEC) domain and the geospatial industry. The main challenge in BIM and GIS integrated application comes from the fundamental data conversion, especially for the geometric information. BIM and GIS use different modeling paradigms to represent objects. The BIM dataset takes, for example, Industry Foundation Classes (IFC) that use solid models, such as boundary representation (B-Rep), swept solid, constructive solid geometry (CSG), and clipping, while the GIS dataset mainly uses surface models or B-Rep. The fundamental data conversion between BIM and GIS is the foundation of BIM and GIS integrated application. However, the efficiency of data conversion has been greatly impaired by the human intervention needed, especially for the conversion of the clipping geometry. The goal of this study is to automate the conversion of IFC clipping representation into the shapefile format. A process-level approach was developed with an algorithm for instantiating unbounded half spaces using B-Rep. Four IFC models were used to validate the proposed method. The results show that (1) the proposed approach can successfully automate the conversion of IFC clipping representation into the shapefile format; and (2) increasing boundary size has no effect on the file size of unbounded half spaces, but slightly increases the producing time of half spaces and processing time of building components. The efficiency of this study can be further improved by using an open-source package, instead of using the low-efficiency packages provided by ArcGIS.