Industry Foundation Classes Schema Research Articles

Prospective Directions in the Computer Systems Industry Foundation Classes (IFC) for Shaping Data Exchange in the Sustainability and Resilience of Cities

Sustainability and resilience in addressing construction’s environmental, social, and economic challenges rely on interoperability. A model-centred approach using standardised information structures like industry foundation classes (IFC) is essential for data sharing in architecture, engineering, construction, and facility management. Achieving complete interoperability across domains requires further research. This review paper focuses on IFC schema, highlighting upcoming developments like IFC 5 and “IFC x”, with a core emphasis on modularisation to enhance domain interoperability, improved links between building information modelling (BIM) and geographic information systems (GIS), along with IoT integration into BIM, cloud-based collaboration, and support for other advanced technologies such as augmented reality (AR), virtual reality (VR), artificial intelligence (AI), and digital twins. Through a critical examination of the IFC and an outlook towards its future enhancements, the research has the potential to offer valuable insights into shaping the trajectory of future advancements within the AEC and facility management sectors. The study’s discoveries could aid in establishing standardised data exchange protocols in these industries, promoting uniformity across projects, facilitating smoother communication, and mitigating errors and inefficiencies. Anticipating enhancements in the IFC could catalyse innovation, fostering the adoption of emerging technologies and methodologies. Consequently, this could drive the creation of more sophisticated tools and procedures, ultimately enhancing project outcomes and operational effectiveness.

The Birth of a New BIM Standard: From PED 2018 to 2023, New Parameters and Workflows "Going Live" for Everyone

Building Information Modelling (BIM) has become the de facto standard for the digital representation of buildings. However, from the pedestrian dynamics perspective, BIM Industry Foundation Classes (IFC) schema specification do not fully support data properties required for two-way data sharing with pedestrian modelling tools. An international team of academic and industry researchers, supported by buildingSMART International (bSI), is developing an Occupant Movement Analysis (OMA) standard. The project is focused on expanding the IFC schema specification to support workflows for pedestrian simulation tools and is close to completion. So far, multiple process maps and a list of data properties synchronised with several representative pedestrian modelling tools have been produced. This list of data properties was then converted into bSI's recommended flexible and machine interpretable Information Delivery Specification (IDS) format for specifying data exchange requirements and to add clarity. Currently, this is undergoing testing and review by the project team. Once completed, it will be submitted to bSI’s committees for review. Also, to support this work, a prototype open-source Add-in has been developed to demonstrate a two-way integrated data sharing between BIM authoring tools and pedestrian simulation tools. This standard will enhance data sharing between BIM authoring and pedestrian modelling tools by facilitating the capturing of the required data and addressing friction in multiple design iterations and reassessment.

IFC data extension for real-time safety monitoring of automated construction in high-rise building projects

Accessing real-time data from the Automated Construction System (ACS) through diverse field sensors holds paramount importance in effective safety management. However, the challenge lies in overcoming inefficient data exchange and information integration. This study seeks to extend the Industry Foundation Class (IFC) standard to seamlessly integrate real-time safety information with the digital model. Our approach involves identifying the essential information required to describe ACS components and safety monitoring items, which is followed by an extension of the IFC schema to create comprehensive descriptions of safety-related data. Additionally, we devise an innovative parameter mapping technique to incorporate dynamic sensory data into corresponding ACS components within the BIM model. We present a case study of a construction project equipped with the ACS, which underscores the feasibility of our approach. Our findings hold substantial practical benefits and establish a robust foundation for future data-driven endeavors within the realm of ACS.

3D object recognition using deep learning for automatically generating semantic BIM data

The successful reuse of Building Information Model (BIM) data is reliant on the use of clearly defined objects. File formats such as the Industry Foundation Classes (IFC) along with classification systems offer approaches to standardising semantic BIM data. Inconsistent application of these standards during BIM authoring results in objects that are unable to be reused across systems. This research proposes a Machine Learning (ML) based alternative for detecting objects and enriching BIM data based on geometrical representations of objects to support interoperability across systems throughout the supply chain. First, an existing dataset of training and test data is modified to correspond with predefined data types from the IFC schema. Second, a convolutional deep belief network is implemented and applied on new testing data from the National BIM Library to identify 3D objects and enabling semantic enrichment of BIM data. Finally, the testing is extended to four real-world industry BIM models. The findings show that the geometric data from emerging BIM object libraries can be used to search and retrieve objects within industry BIM models based on geometric rather than semantic data.

Linked data to streaming data sensors sources for direct access

Goal: Industrial operations are complex, and data sensors assure safety and reliable information for production improvements. Multiple stakeholders can take advantage of data acquisition for post-analysis and process control. Providing users and systems with friendly access to operating data is fundamental to the digital transition in the industry 4.0 scenario. Linking data and systems over ontologies and Industry Foundation Classes will boost supply chain performance in many layers. This paper presents the concept of valid data points over Uniform Resource Identifiers for sensor time-series into triples stores via Application Programming Interfaces. Design/Methodology/Approach: A streaming data source approach to integrating industrial sensor data and sharing it via Uniform Resource Identifiers is developed and tested using Node-Red with multiple data connection types, such as the Industry Foundation Classes and open-source time series databases. Results: The detailed proof of concept presented valid the feasibility of sharing sensor data via Uniform Resource Identifiers. The findings provide a backbone of a system able to interop Message Queuing Telemetry Transport data, Resource Description Framework datasets and Industry Foundation Classes schema. Limitations of the investigation: The system envisaged was tested using simulated data. However, it is expected to have similar results from real data use. Nevertheless, more research will be needed to implement more features, such as three-dimensional object integration. Practical implications: The solution designed and tested presented can be used in practice for companies that desire to expand via linked data shareability and interoperability. Also, researchers can advance the solution for specific features, such as creating an open-source data query and manipulation language. Originality/Value: This paper examines future deployments of systems-to-systems interoperability targeting user-friendly data shareability. It is meant to be useful for industrial and academic developments.

Perspectives of 3D Probabilistic Subsoil Modeling for BIM

Building information modeling (BIM) in the planning and construction of infrastructure projects, such as roads, tunnels, and excavations, requires the generation of comprehensive 3D subsoil models that encompass relevant geological and geotechnical information. Presently, this process relies on the deterministic interpolation of discrete data points obtained from exploratory boreholes and soundings, resulting in a single deterministic prediction. Commonly employed interpolation methods for this purpose include radial basis function and kriging. This contribution introduces probabilistic methods for quantifying prediction uncertainty. The proposed modeling approach is illustrated using simple examples, demonstrating how to use sequential Gaussian and Indicator Simulation techniques to model sedimentary processes such as erosion and lenticular bedding. Subsequently, a site in Munich serves as a case study. The widely used industry foundation classes (IFC) schema allows the integration of the model into the BIM environment. A mapping procedure allows transferring voxel models to the IFC schema. This article discusses the significance of incorporating uncertainty quantification into subsoil modeling and shows its integration into the BIM framework. The proposed approach and its efficient integration with evolving BIM standards and methodologies provides valuable insights for the planning and construction of infrastructure projects.

Integration of Building Information Modeling Interoperability into Nonlinear Finite Element Analysis of Bridge Substructures

Acceptance of building information modeling (BIM) throughout the bridge industry is widely recognized as inevitable. However, while adoption of BIM technologies has proliferated throughout the building industry, advances pertaining to BIM for bridges and other structures remain underway. The present study aims to increase the potential for integrating BIM processes into software packages that possess capabilities for nonlinear finite element analysis (FEA) of bridge substructures. Moreover, the present study is intended to galvanize stakeholders within the area of soil–structure interaction (SSI) modeling and analysis to more effectively participate in interoperability workflows as part of bridge design. A proof-of-concept exporter tool was formulated in a modular manner to robustly export finite element model data stored in a selected SSI analysis package into the Industry Foundation Classes (IFC) standard, with the IFC standard chosen as the target schema owing to its widespread usage in the construction industry. The ability of the exporter tool to—with fidelity—convert a model from the selected analysis software to the IFC standard is showcased through an illustrative case study. In carrying out the case study, collections of geotechnical modeling parameters were identified that, while being common to numerous nonlinear SSI analysis packages, are not present in the existing IFC schema. Inclusion of these parameters in the IFC schema is proposed, serving to: 1) lower the barrier for entry of SSI modeling and analysis stakeholders to take part in interoperability processes and 2) encourage adoption of novel BIM processes in the bridge industry.

INTEGRATION OF STRUCTURAL INFORMATION WITHIN A BIM-BASED ENVIRONMENT FOR SEISMIC STRUCTURAL E-PERMITS

The assessment of the structural safety of buildings, with the related outcomes and other structural information, is typically reported in un-structured sets of documents (tables, drawings, reports, etc.). This happens even if Building Information Modelling (BIM) workflows, platforms, and standards are adopted. Generally, the BIM database provides input data for the structural design, but most of the data produced by structural designers, according to the structural codes, do not fully integrate into the BIM database along with other context-related information. These data are not easily recorded, especially in openBIM standard file formats such as Industry Foundation Classes (IFC). In the context of digital procedures for permit applications pertaining to seismic structural engineering, the authors propose an openBIM approach for the integration of structural information to support the activities of building authorities’ bodies (BABs). The proposed framework has led to the development of an Information Delivery Manual (IDM) and a Model View Definition (MVD), considering the IFC schema, for the integration and exchange of information within a BIM-based environment. Successively, the authors implemented the proposed IDM/MVD solution in a case study that provided an effective workflow for innovative future delivery of necessary information to building authorities to obtain seismic authorization permits.

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.

An IFC Approach for BIPV Technical Pre-design Consideration

The increasing demand for nearly-Zero Energy Buildings contributes to a broader discussion of implementing building-integrated photovoltaics (BIPV) on building envelopes. Existing research indicates that BIPV products should be digitally represented in Building Information Modeling (BIM) to facilitate the design process. The Industry Foundation Classes (IFC) schema as data exchange standard needs to support the relevant BIPV use cases to enable the exchange of relevant BIM data between stakeholders. However, there is a lack of clear identification of BIPV use cases which are needed as a basis for assessing IFC’s ability to capture and represent BIPV products digitally. The identification of BIPV use cases is also necessary for the proper development of a Model View Definition (MVD) for IFCs in the BIPV domain. This study uses the technical pre-design consideration as sample use case to demonstrate the processes of developing an MVD for BIPV digital products in the Australian context. A three-step research approach is employed, including a collection of use cases through a literature review and interviews, defining exchange requirements and proposing an initial MVD based on IFC4 ADD2 TC1. This paper contributes to the BIPV area by providing a BIPV use case description for the Technical Pre-design Consideration use case in the Australian context and identifying existing challenges in the current IFC schema related to representing BIPV product information.

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.

GEOREFERENCING IN IFC: MEETING THE REQUIREMENTS OF INFRASTRUCTURE AND BUILDING INDUSTRIES

Abstract. The problem of georeferencing building information modelling (BIM) models is complex and in need of a comprehensive solution. We focus on the open BIM data format Industry Foundation Classes (IFC) and its georeferencing implementation. The requirements voiced by the domain experts during recent years have been collected and analysed. While IFC already covers some of the concepts, we propose an extension to the IFC schema to handle the inadequacy. Our proposal composes of two new entities: one supports geographic coordinate reference systems (CRSs) and the other enables a rigid transformation of BIM geometries. We showcase the possibilities with three examples, one for each of the required scenarios. The improvements assure much-needed semantically clear definitions of the georeferencing concept within the IFC data model. As such, the interpretation of IFC data content is unambiguous for stakeholders and software implementers.

Digitalization of culturally significant buildings: ensuring high-quality data exchanges in the heritage domain using OpenBIM

Cultural heritage building information models (HBIMs) incorporate specific geometric and semantic data that are mandatory for supporting the workflows and decision making during a heritage study. The Industry Foundation Classes (IFC) open data exchange standard can be used to migrate these data between different software solutions as an openBIM approach, and has the potential to mitigate data loss. Specific data-exchange scenarios can be supported by firstly developing an Information Delivery Manual (IDM) and subsequently filtering portions of the IFC schema and producing a specialized Model View Definition (MVD). This paper showcases the creation of a specialized IDM for the heritage domain in consultation with experts in the restoration and preservation of built heritage. The IDM was then translated into a pilot MVD for heritage. We tested our developments on an HBIM case study, where a historic building was semantically enriched with information about the case study’s conservation plan and then checked against the specified IDM requirements using the developed MVD. We concluded that the creation of an IDM and then the MVD for the heritage domain are achievable and will bring us one step closer to BIM standardisation in the field of digitised cultural buildings.

A CONCEPTUAL MODEL FOR IFC-BASED DELINEATION OF CONDOMINIUM RIGHTS IN TURKEY: INITIAL EXPERIMENTS

Abstract. Owing to the increasing existence of multistorey buildings and infrastructures in the built environment, there is a need for three-dimensional (3D) land administration systems (LAS). Regarding this, condominium rights in real-estate properties are needed to be represented as 3D for preventing misinterpretations with regards to who is responsible for or has ownership in which parts of the buildings. Digitalizing the public services appears in current strategies of governments and administrations since it contributes to transparency, speed, and accurateness in the processes. Building permitting that contains obtaining the occupancy permit is a vital one of these public services. With the even-increasing adaptation of Building Information Modelling (BIM), a whole raft of Building Information Models (BIMs) are created to use in digital building permitting. Thus, a significant opportunity for 3D delineation of condominium rights comes out of the reuse of these BIMs, especially their Industry Foundation Classes (IFC) data. In this sense, this paper puts forward an approach that includes developing the conceptual model to depict condominium rights and linking that model with the IFC schema. The applicability of the approach is demonstrated by using a floor of a simple building. The study shows that IFC-based representation of condominium rights can be beneficial for the transition to 3D LAS in Turkey.

Extending the IFC Standard to Enable Road Operation and Maintenance Management through OpenBIM

Open Building Information Modelling (OpenBIM) is a collaborative project management process. Its application to road infrastructures is currently limited. OpenBIM standards for infrastructure are still under development. One of these standards is the Industry Foundation Classes (IFC), which is a data architecture for modelling infrastructure projects. The current and upcoming releases of IFCRoad focus on structuring data for the design and construction phases of an infrastructure’s lifecycle. Semantics of the O&M process phase are not fully integrated within these standards. This paper proposes an extension of the IFC schema to enrich this standard with semantics inherent in the O&M phase of road infrastructures. This extension, based on IFCInfra4OM ontology, allows the OpenBIM process to be fully applied to road infrastructures. Its implementation on a case study relative to the A7 Agadir–Marrakech Highway in Morocco enables, on the one hand, analysis and compliance with O&M management requirements on the basis of a single container: the IFC-BIM-based model. On the other hand, it allows comparison of the OpenBIM process with that of ClosedBIM for the integration of O&M data into BIM for a road infrastructure.

An IFC schema extension for BIM-based description of wastewater treatment plants

Building information modeling (BIM) may advantageously be used to support life-cycle management of engineering structures. The Industry Foundation Classes (IFC) are a standardized BIM data format issued by the International Organization for Standardization to describe engineering structures, such as buildings, tunnels, and bridges. Although often employed for describing basic features of structures, the IFC standard is not capable of sufficiently describing the planning procedure of wastewater treatment plants, which is determined by functional aspects. This paper presents an IFC schema extension that supports BIM-based planning of wastewater treatment plants. A semantic model, serving as a formal basis for the IFC schema extension, is defined that contains the semantics describing the information used for planning of wastewater treatment plants. The IFC schema extension proposed in this study enables BIM-based description of wastewater treatment plants in compliance with the IFC standard, and it may serve as basis for wastewater treatment plant simulations.

The Extension of IFC For Supporting 3D Cadastre LADM Geometry

The growth of densely populated urban areas has caused traditional cadastral registration systems to face many difficulties in representing complex and multilevel property situations on 2D maps. These challenges, combined with the rapid development of 3D technologies, have forced the research and progress of 3D cadastre systems. The aim of this study is to investigate how a Building Information Model (BIM) can be used as a data source for the Land Administration Domain Model (LADM) based 3D cadastre system, and how that process can be improved. The Industry Foundation Classes (IFC) format and the LADM-based model were selected because both are international open standards that have a significant impact in their own domain. The data sample for the 3D cadastre system was extracted from a BIM model. The paper proposes an IFC format extension which makes it possible to define 3D geometry according to the LADM standard. In order to demonstrate this extension, the West 65 residential and business complex, Belgrade, was selected as a case study. The IFC format extension presented here is a step towards data harmonization between BIM in the IFC format and 3D cadastre systems; it should provide more suitable data in the current IFC schema and enable easy data flow between BIM projects and 3D cadastral data.

BIM-Based Description of Intelligent Transportation Systems for Roads

Intelligent transportation systems (ITS) provide safer, greener, and more convenient mobility, while reducing the impact on the environment. In recent years, simulation platforms have been employed to study ITS applications, mostly focusing on traffic-related simulations. Despite several research studies on ITS applications and simulation platforms, formal semantic descriptions of intelligent transportation systems have not been addressed yet. In this paper, a semantic model describing intelligent transportation systems for roads is proposed. The semantic model is devised to provide a basis for designing ITS simulation platforms. Building upon the semantic model, an extension to an open building information modeling (BIM) standard, i.e., the Industry Foundation Classes (IFC) schema, is presented. The IFC schema extension is verified and validated using a BIM-based simulation scenario of ITS for roads. It is shown that the proposed IFC-compliant description of ITS for roads provides a formal basis for generating BIM-based simulations and hence facilitates ITS infrastructure modeling in BIM projects. It is concluded that the present work represents a cornerstone for designing BIM-based ITS simulation platforms. In future endeavors, potential standardization and formalization efforts may be discussed.

An Approach of Automatic SPARQL Generation for BIM Data Extraction

Generally, building information modelling (BIM) models contain multiple dimensions of building information, including building design data, construction information, and maintenance-related contents, which are related with different engineering stakeholders. Efficient extraction of BIM data is a necessary and vital step for various data analyses and applications, especially in large-scale BIM projects. In order to extract BIM data, multiple query languages have been developed. However, the use of these query languages for data extraction usually requires that engineers have good programming skills, flexibly master query language(s), and fully understand the Industry Foundation Classes (IFC) express schema or the ontology expression of the IFC schema (ifcOWL). These limitations have virtually increased the difficulties of using query language(s) and raised the requirements on engineers’ essential knowledge reserves in data extraction. In this paper, we develop a simple method for automatic SPARQL (SPARQL Protocol and RDF Query Language) query generation to implement effective data extraction. Based on the users’ data requirements, we match users’ requirements with ifcOWL ontology concepts or instances, search the connected relationships among query keywords based on semantic BIM data, and generate the user-desired SPARQL query. We demonstrate through several case studies that our approach is effective and the generated SPARQL queries are accurate.

A geometric deep learning approach for checking element-to-entity mappings in infrastructure building information models

Abstract Data interoperability between domain-specific applications is a key prerequisite for building information modeling (BIM) to solidify its position as a central medium for collaboration and information sharing in the construction industry. The Industry Foundation Classes (IFC) provides an open and neutral data format to standardize data exchanges in BIM, but is often exposed to data loss and misclassifications. Concretely, errors in mappings between BIM elements and IFC entities may occur due to manual omissions or the lack of awareness of the IFC schema itself, which is broadly defined and highly complex. This study explored the use of geometric deep learning models to classify infrastructure BIM elements, with the ultimate goal of automating the prechecking of BIM-to-IFC mappings. Two models with proven classification performance, Multi-View Convolutional Neural Network (MVCNN) and PointNet, were trained and tested to classify 10 types of commonly used BIM elements in road infrastructure, using a dataset of 1496 3D models. Results revealed MVCNN as the superior model with ACC and F1 score values of 0.98 and 0.98, compared with PointNet's corresponding values of 0.83 and 0.87, respectively. MVCNN, which employs multiple images to learn the features of a 3D artifact, was able to discern subtle differences in their shapes and geometry. PointNet seems to lose the granularity of the shapes, as it uses points partially selected from point clouds.