BIM-GIS ORIENTED INTELLIGENT KNOWLEDGE DISCOVERY

Success in construction projects fundamentally depends on exceptional project management, with project cost management (PCM) being one of the key components. However, PCM often faces constraints such as outdated data and data inaccuracies throughout the project’s lifecycle, which consequently undermine its reliability. Recently, 5D Building Information Modelling (BIM) is gaining attention as an innovative work process that could facilitate PCM enhancement. Despite the potential of 5D BIM to address the PCM issues, it is found that technology struggles with certain PCM data complexities; thus, suggesting that big data analytics (BDA) might be beneficial if used concurrently with 5D BIM in providing solutions. Nevertheless, the linkage between 5D BIM components and big data (BD) attributes remains scantily mapped. Therefore, a systematic mapping between these domains is necessary as a forerunner to manifest their relationship. In order to address this gap, this research employs a systematic literature mapping method with the aim to illustrate the associations and the potential synergies between 5D BIM and BD attributes. The findings suggest that there is a distinct theoretical connection between them, highlighting the need for further exploration and investigation for practical implementation. This research serves as a milestone in understanding the interplay between 5D BIM and BD attributes, paving the way for more effective integration in the current industry practices.

Exploring the rate of adoption and implementation depth of building information modeling (BIM): A case of Kuwait

The aging population is growing drastically all over the world. With the advent of the global era, universal design is garnering considerable interest, as the number of multicultural families is increasing, and various user classes are being created. In addition, with the advances in construction technology, architectural design is becoming more diverse, and convenience facilities are also getting distributed in various ways. As a result, more buildings need to apply universal design, indicating that various architectural information and universal design for the user class are required. Various data are needed for universal design evaluation, but there is a limit to evaluating with two-dimensional (2D) drawings. However, the limitations of 2D drawings can be overcome via building information modeling (BIM) combined with architectural data, which remarkably simplifies the universal design evaluation. This study was conducted with the aim to analyze architectural information by extracting architectural elements necessary for universal design evaluation from BIM data. It was confirmed that the calculations for universal design evaluation can be performed by 3D shape or attribute analysis using BIM data and computer programming. In order to create an automated evaluation algorithm for universal design, the evaluation methods were classified according to the universal design evaluation guide, based on building users and user diversity. In addition, even if the evaluation methods were the same by location, different points were classified by location, and evaluation items and information necessary for the evaluation were organized by category for each facility. Through this classification, we created an algorithm with seven types of methods for extracting the BIM data and comparing them by evaluation method for an automated analysis. In addition, an analysis was performed directly on the BIM design sample model using an automated evaluation algorithm. Although there were various architectural objects in the design data, evaluation was possible using algorithms. By applying the universal design evaluation and BIM data evaluation methods, we could confirm that the BIM-based universal design automation evaluation method prevents human error and is thus superior to the existing evaluation methods. Further, the automation evaluation method can contribute to BIM activation as the BIM data can be used in various studies such as design certification evaluation and automation analysis.

Smart building is a rising interdisciplinary research field that aims to improve the monitoring, management, and maintenance of buildings. The authors present an innovative solution for combining building information modeling (BIM) data with ambient information collected by heterogeneous devices deployed in the building. To collect environmental information, they exploit a distributed software architecture. It enables interoperability between heterogeneous data sources--either physical devices, such as sensor nodes, or third-party software such as Archibus--where building information resides. On top of this infrastructure, they developed an Android-based application that presents environmental building information integrated with BIM data in an augmented and virtual reality environment. The proposed solution gives users awareness about building conditions and energy consumption.

Purpose The recent research trend of building information modelling (BIM) involves interoperability and issues pertaining to the design, construction, operations, and maintenance phases of a building. However, few researchers are concerned with problems encountered in the last two phases of the building life cycle. Since BIM has been widely used in the design and construction phases, further expanding the BIM data stream to the post-construction phase can not only establish a consistent, shared database for information exchange between the phases but assist in current facility management applications. This research reconceptualises BIM with object-oriented thoughts to a space-based representation, and tries to construct an interface between BIM and existing facility management software. Method Model-driven architecture (MDA) is one of the modern software design approaches. With its foundation – meta-object facility (MOF) – and model transformation, MDA provides an ideal solution for easily maintaining the interoperability. In this research, a MOF of a building is constructed by imitating the MDA approach, encapsulating BIM data and providing an interface for external facility management software. This MOF of a building is designed with spatial interference due to the maintenance and repair work is usually based on the space. Results & Discussion A conceptual demonstration of disaster mitigation is conducted to test the feasibility of using MDA to encapsulate BIM data for extended applications. Furthermore, the expected results are reconstructing maintenance records to a space-based database for a better software design and a solution for interoperability.

Conventional construction scheduling techniques often fall short due to inefficiencies, the prevalence of human error, and the lack of reliable scheduling data. Despite efforts to obtain better scheduling data and automate the process using Building Information Modelling (BIM) as a primary source of information, challenges persist. BIM models contain inconsistencies that can compromise their scheduling effectiveness. Moreover, existing automation efforts face obstacles, including complexity and scalability issues. These efforts frequently overlook the intricacies of accurately modelling construction tasks, neglecting resource considerations, subprocesses, and structured information management, which further complicates the creation of reliable and efficient construction schedule data. This research proposes a framework designed to systematically obtain scheduling data in an automated manner, aligning with a Work Breakdown Structure (WBS) to ensure organisational clarity. By incorporating subprocesses and focusing on resource constraint calculations and balancing. Furthermore, the framework structures scheduling data into a CSV format, facilitating easier analysis and integration with project management tools. The research follows the Design Science Research methodology. This multi-stage framework integrates BIM data extraction, automated element labelling, creation of a custom WBS, construction sequence, and resource balancing. The framework was developed using Python coding and libraries, facilitating seamless transitions between stages without manual intervention. The framework's performance is evaluated using 4D BIM software, assessing the generated data and logic in a girder bridge projects. This innovative framework enhances the accuracy and efficiency of construction data scheduling through automation. It reduces manual intervention, organises data effectively, and improves project timeline reliability. The use of 4D BIM further illustrates the practical application of this data in bridge projects, showcasing a scalable and robust contribution to construction automation.

Currently, cloud computing and big data are largely applied in smart construction, or so-called industrial Internet of Things 4.0. Building Information Model (BIM) performs as an elemental information and data unit, which is extensively employed in entire construction processes (lifespan) and inter-acted with various entities including investors, employers, design institutes, construction companies, and monitors. They thus can achieve quantitative computing, measurement, and managements by sharing BIM data. The accumulation of BIM data will finally approach to a big data for construction intelligence. However, sharing BIM big data may be subtle in terms of privacy leakage, since BIM data may enclose the critical infrastructure information, homeland security data, structure parameters, and design intellectual property. It thus is of urgent importance to protect privacy in the BIM data sharing. In this paper, we propose a blockchain based method to protect data privacy in BIM data sharing, which can be applied for guaranteeing the information security in next generation industrial Internet of Things for smart construction.

- Building Information Modelling (BIM) has emerged as a transformative enabler for modular steel construction by providing parametric modelling, coordinated detailing, digital fabrication integration, and 4D construction sequencing. Modular steel systems require high accuracy in design, fabrication, logistics, and assembly, making BIM indispensable for reducing rework, improving coordination, and enabling just-in-time production. This paper examines the integration of BIM within modular steel construction, focusing on prefabrication accuracy, clash-free detailing, sequencing simulation, and digital manufacture. The study includes a comprehensive literature review, a methodology grounded in BIM-enabled workflows, and analysis of two major case studies Chennai International Airport Terminal T2 and Shanghai Tower. Findings indicate that BIM significantly improves productivity, reduces site conflicts, minimizes waste, and enhances assembly predictability, particularly in the Indian context where BIM adoption faces challenges such as limited skills, high costs, and low SME readiness. The paper concludes with strategic recommendations for India’s modular steel industry and outlines future research directions. Key Words: Building Information Modelling (BIM), Modular Steel Construction, Prefabrication, Digital Fabrication, 4D BIM, Clash Detection, SMEs, Coordination, Steel Structures

As the AEC industry strives to establish integrated knowledge exchange protocols utilizing building information models (BIMs), structural engineering practices of all sizes will profit from the ability to effectively communicate with the design team supported by a strongly integrated structural design process. At Thornton Tomasetti, custom tools are developed to automate the exchange of structural design data between 2D and 3D analysis models and BIMs. These tools are unique because they allow the engineer to manage partial models and data sets as independent sub-systems of complete virtual models. These sub-systems are often described in plan or elevation, while their counter parts reside in the 3D setting of the overall BIM. Custom automation of processes at Thornton Tomasetti helps to meet deadlines, exceed expectations of clients, and increases the quality of the work product. We cite three examples illustrating custom usage of application programming interfaces (APIs) and address typical challenges met when pursuing in-house development projects. The case studies include the utilization of conventional CAD documents as basic structural information models (SIMs), the automatic assembly of structural elements of complete towers in a BIM, and efficient bent management assisting the design process of stadiumlike structures. 1. BIM METHODOLOGY IN THE AEC ENVIRONMENT Following building information modeling (BIM) methodology, members of the AEC design team communicate by exchanging knowledge through a virtual model of the project, usually referred to as “BIM.” Currently, BIM compliments the traditional information flow - drawings. The industry trend moves toward using BIM as the primary tool, and if needed, drawings can be compiled as views or reports on demand. Building information modeling methodology focuses primarily on the following two objectives: a) Visualization and Coordination: Allowing the members of the AEC design team to virtually construct a digital model of the project, very similar to the WYSIWYG concept (“what you see is what you get”) in word processing. A model has to look right, be measurable, allow an assessment of constructability, and “know” when parts

The manual creation of Building Energy Performance Simulation (BEPS) models is time-consuming and error-prone, hindering the implementation of energy-efficient building designs. This paper explores how to automate the generation of BEPS models from Building Information Modeling (BIM) data while addressing challenges of data imperfection and tool compatibility. bim2sim is presented as an open-source Python framework with a modular plugin architecture that processes Industry Foundation Classes (IFC) files to generate simulation models for various tools, including Modelica/TEASER and EnergyPlusWe present bim2sim , an open-source Python framework with a modular plugin architecture that processes Industry Foundation Classes (IFC) files to generate simulation models for various tools including Modelica/TEASER and EnergyPlus. The application to a non-residential building case study demonstrates the framework’s capability to produce functional simulation models at different levels of detail with significant time savings, reducing the time for generating simulation results from a BIM model to less than one hour. The framework benefits architects, building services engineers, and simulation engineers by streamlining the simulation workflow while maintaining OpenBIM compatibility. Future research should address remaining limitations in geometry processing and material mapping to further facilitate seamless information exchange between building design and simulation domains. • bim2sim framework converts BIM to simulation-ready building energy models, reducing manual processing and errors. • bim2sim is built as open-source Python framework with modular plugins supporting multiple simulation tools and domains. • Demonstration with two plugins: TEASER (Modelica) for annual energy demands and EnergyPlus for thermal/comfort analysis. • Efficient model conversion (<1hr), robust to imperfect IFC data while maintaining OpenBIM compatibility.

Since 2015, a 13-week core course “Integrated Building Project Development (IBPD)” was launched annually for final year students of all undergraduate programmes of the Department of Architecture and Civil Engineering of the City University of Hong Kong. These undergraduate programmes cover most disciplines of the construction industry—architectural studies, civil and structural engineering, building services engineering, surveying, and construction engineering and management. From 2018 onwards, students are required to use Building Information Modelling (BIM) across all disciplines in the project development process of this course. A BIM project execution plan on Client’s BIM requirements, the scope of BIM implementation and the required BIM deliverables in this course is provided to students. A BIM server that supports in-campus and remote access was built for students to store, retrieve and archive their digital files so that they can practise BIM communication and data exchange on a centralised platform. This paper shares the successful execution of the BIM project execution plan, under the framework of the interdisciplinary BIM (iBIM) implementation and the BIM server architecture, by the students.KeywordsUndergraduate programmesIntegratedMultidisciplinaryBuilding Information Modelling (BIM)

Cost overruns and schedule delays are persistent challenges in the construction phase. Developing a feasible and optimized construction plan is essential for efficient resource allocation and reliable cost estimation. Despite technological advances, many planning, inspection, and progress control processes remain manual and time-consuming. Although scheduling tools like the Critical Path Method (CPM) are common, key inputs such as task durations, sequences, and resource needs are still manually determined, with limited integration into 3D models and minimal automation. Although 4D Building Information Modeling (BIM) offers significant potential, its adoption remains limited, particularly in some developing countries, due to high initial costs and implementation challenges. This paper proposes a framework that automates the development of optimized construction methods for reinforced concrete buildings. Using 3D BIM data, the framework generates a Work Breakdown Structure (WBS), produces detailed schedules, and links them with the BIM model to simulate progress, plan daily resource use, and minimize consumption. By integrating 4D BIM, the system enables the visualization of construction sequences, the evaluation of alternative methods, and the comparison of multiple execution scenarios based on time and resource constraints. The framework supports early decision-making, reduces planning time, and improves project delivery outcomes.

Productivity is a critical performance indicator of the construction industry, and thus warrants effective and efficient construction productivity measurement (CPM). Building information modelling (BIM), a digital representation of the building process, plays a significant role in effective and efficient CPM. Considering the high mandatory requirements for enhancement in construction productivity measurement, this paper aims to review the state-of-the-art literature on BIM-integrated CPM, to identify gaps in the existing body of knowledge and explore future research trends. The aim is achieved through a systematic literature review and bibliometric analysis where the data are retrieved from Web of Science, Scopus, and Google Scholar and proposes future research directions. In total 260 publications were identified from the initial search, and 56 were shortlisted for full-text analysis after several levels of screening including duplication, title and abstract checking. Finally, 21 were narrowed yielded for detailed review for this study. The results mapped the yearly publication trend, publications by source and the co-occurrence of terms. The findings help to identify a suite of BIM-integrated CPM methods used in the construction industry and provide a foundation for future research in CPM. A framework is developed to illustrate the knowledge gap and future directions identified in this study. Accordingly, the findings revealed that existing studies on utilising BIM for CPM are limited to only 3D and 4D BIM. Further, there is a lack of studies on the feasibility of using BIM for CPM, fully automated BIM integrated CPM tools and real-time CPM through BIM.

Building Information Modelling (BIM) is a technological revolution developed in the construction industry. The implementation of BIM using Tekla Structure software helps overcome problems in the 3-story steel building construction project. Integration of the structural analysis software and Tekla Structure BIM, making the design phase efficient. Detailed drawings generated at the design stage using analysis software and BIM, lead to efficient construction exploration and evaluation. Tekla Structure produces detailed drawings and a list of required materials, which can help contractors in project management. Simultaneous management of activities between site and workshop, providing the advantage of project completion on schedule. Procurement of materials and errors during construction can be minimized, thereby optimizing project costs.

Delay and Disruption is a common occurrence in construction projects. The challenges of forensic schedule analysis and the evaluation of the extent of project delay increase with the degree of complexity of a project. The occurrence of multiple concurrent delays, secondary effects and the cumulative impact of delay and disruption events can render the establishment of entitlement to extension of time and reimbursement a difficult task. In order for the claiming party to receive compensation for project delay and disruption, causation, liability and quantum have to be demonstrated and proven. Advances in technology have made a shift from conventional delay analysis methods towards delay and disruption analysis supported by Building Information Models possible. Research and application of Building Information Models has increased in recent years, exploring information coordination on multiple dimensions. Linking the fourth dimension of time to a 3D model enables the user to visualize a representation of the construction process. The application of 4D simulation in forensic schedule analysis is a great tool for the visualization of delay events and their effects on the project schedule and the construction process. Although 4D Building Information Models are able to assist forensic schedule analysis, the identification of the cause and effect relationship of delay events of complex construction works, requires an expert who is not only familiar with the software tools but has also experience in delay analysis and is able to clearly determine the accuracy of the produced data. 4D Building Information Models can simulate a high level of project performance, producing great quantities of data. The role of the delay analyst is to identify the relevant facts from the great quantities of data simulated in the 4D model, in order to support his findings of entitlement, causation and resulting damages. The purpose of this paper is to investigate the use of 4D Building Information Modelling in delay and disruption claims and outline the expertise required to perform the forensic schedule analysis.