Revit and IFC with ChatGPT | Automated ETL with CAD (BIM) Data
21 March 2024
Big Data in Construction
19 May 2024

Revit and IFC in Unreal Engine, Unity, Oculus – VISUALIZATION, RENDERING, METAVERSE, GAME DESIGN

🌊 Standard rendering in CAD (BIM) programs often falls short of visualization quality, but game engines such as Unreal Engine and Unity have revolutionized architectural and design visualization. These engines offer fast rendering and intuitive light, material, and geometry settings that greatly improve the visualization process. Clients can now explore virtual building models by interacting with elements such as lighting and furniture in real time, improving their understanding and engagement. Unreal Engine enables metaversions, turning 3D virtual worlds into major social centers.

To use these advanced visualization tools, you need to convert CAD (BIM) data into open formats such as USD, DAE, GLTF and OBJ. The DataDrivenConstruction (DDC) converter facilitates this by converting IFC and Revit files into compatible formats for use in Unreal Engine, Oculus, and Unity without requiring an internet connection. This capability greatly enhances the rendering, visualization and simulation capabilities of architectural and design work:

🌑 Unreal Engine lets you create interactive 3D, augmented (AR) and virtual (VR) reality applications from 3D CAD (BIM) models

🌑 Visualization or simulation of car and people movement can be set up literally in a few clicks. Weather and time are also easily customizable

🌑 Free engines allow you to plug in artificial intelligence algorithms that visually allow you to reproduce simulations in real scenes rather than on paper

🌑 Using Unity and the #ML-Agents toolkit, you can create AI environments that are physically, visually, and cognitively rich

🌑 With Unity #MachineLearning Agents, you no longer "code" emergent behavior, but teach intelligent agents to "learn" using a combination of deep reinforcement learning and simulation learning

🌑 Unreal Engine allows users to actually create their own software (which will probably soon change the way we approach data tools).

Data in non-parametric IFC and proprietary RVT formats, but in open files (XLSX contains all parameters and DAE contains geometric representations of project entities) allow you to make a cast of the entire project and store all project data in open files that don't require third-party algorithms or proprietary products to open.

📈 Streamline your toolkit, strip away the complexity from your workflows, and master the art of utilizing open and straightforward data!

📥 Free DDC converters for Revit (2015-2022) and IFC2x3:
https://datadrivenconstruction.io/index.php/convertors/

 

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    Focus Areas

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    • ALL THE CHAPTERS IN THIS PART
    • A PRACTICAL GUIDE TO IMPLEMENTING A DATA-DRIVEN APPROACH (8)
    • CLASSIFICATION AND INTEGRATION: A COMMON LANGUAGE FOR CONSTRUCTION DATA (8)
    • DATA FLOW WITHOUT MANUAL EFFORT: WHY ETL (8)
    • DATA INFRASTRUCTURE: FROM STORAGE FORMATS TO DIGITAL REPOSITORIES (8)
    • DATA UNIFICATION AND STRUCTURING (7)
    • SYSTEMATIZATION OF REQUIREMENTS AND VALIDATION OF INFORMATION (7)
    • COST CALCULATIONS AND ESTIMATES FOR CONSTRUCTION PROJECTS (6)
    • EMERGENCE OF BIM-CONCEPTS IN THE CONSTRUCTION INDUSTRY (6)
    • MACHINE LEARNING AND PREDICTIONS (6)
    • BIG DATA AND ITS ANALYSIS (5)
    • DATA ANALYTICS AND DATA-DRIVEN DECISION-MAKING (5)
    • DATA CONVERSION INTO A STRUCTURED FORM (5)
    • DESIGN PARAMETERIZATION AND USE OF LLM FOR CAD OPERATION (5)
    • GEOMETRY IN CONSTRUCTION: FROM LINES TO CUBIC METERS (5)
    • LLM AND THEIR ROLE IN DATA PROCESSING AND BUSINESS PROCESSES (5)
    • ORCHESTRATION OF ETL AND WORKFLOWS: PRACTICAL SOLUTIONS (5)
    • SURVIVAL STRATEGIES: BUILDING COMPETITIVE ADVANTAGE (5)
    • 4D-6D and Calculation of Carbon Dioxide Emissions (4)
    • CONSTRUCTION ERP AND PMIS SYSTEMS (4)
    • COST AND SCHEDULE FORECASTING USING MACHINE LEARNING (4)
    • DATA WAREHOUSE MANAGEMENT AND CHAOS PREVENTION (4)
    • EVOLUTION OF DATA USE IN THE CONSTRUCTION INDUSTRY (4)
    • IDE WITH LLM SUPPORT AND FUTURE PROGRAMMING CHANGES (4)
    • QUANTITY TAKE-OFF AND AUTOMATIC CREATION OF ESTIMATES AND SCHEDULES (4)
    • THE DIGITAL REVOLUTION AND THE EXPLOSION OF DATA (4)
    • Uncategorized (4)
    • CLOSED PROJECT FORMATS AND INTEROPERABILITY ISSUES (3)
    • MANAGEMENT SYSTEMS IN CONSTRUCTION (3)
    • AUTOMATIC ETL CONVEYOR (PIPELINE) (2)

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    057 Speed of decision making depends on data quality

    Today’s design data architecture is undergoing fundamental changes. The industry is moving away from bulky, isolated models and closed formats towards more flexible, machine-readable structures focused on analytics, integration and process automation. However, the transition...

    060 A common language of construction the role of classifiers in digital transformation

    In the context of digitalization and automation of inspection and processing processes, a special role is played by classification systems elements – a kind of “digital dictionaries” that ensure uniformity in the description and parameterization...

    061 Masterformat, OmniClass, Uniclass and CoClass the evolution of classification systems

    Historically, construction element and work classifiers have evolved in three generations, each reflecting the level of available technology and the current needs of the industry in a particular time period (Fig. 4.2-8): First generation (early...

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    🚀 Welcome to the future of data in construction!

    You're taking your first step into the world of open data, working with normalized, structured data—the foundation of data analytics and modern automation tools.

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    🚀 Welcome to the future of data in construction!

    You're taking your first step into the world of open data, working with normalized, structured data—the foundation of data analytics and modern automation tools.

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    This short assessment will help you identify your company's data management pain points and offer solutions to improve project efficiency. It takes only 1–2 minutes to complete and you will receive personalized recommendations tailored to your needs.

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    Chapters 5.2, 7.2 – QTO Automation, ETL with Python:

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    Chapters 4.1, 8.1–8.2 – From CAD (BIM) to Storage & Analytics:

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    Chapters 7.3, 10.2 – Building ETL Pipelines + Strategic Integration:

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    Module 8 – Converting Unstructured CAD into Structured Formats 
    • From IFC/Revit to tables
    • Geometric vs semantic data
    • Tools for parsing and transforming CAD models

    Module 13 – Key Stages of Transformation 
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    Module 8 – Integrating Diverse Data Systems and Formats
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    Revit and IFC in Unreal Engine, Unity, Oculus – VISUALIZATION, RENDERING, METAVERSE, GAME DESIGN
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