About the Project

Research Overview

The integration of generative AI into architecture is transforming early-stage design processes, particularly by enabling rapid and automated floorplan generation. These tools increase efficiency by exploring large design spaces and producing multiple layout options in a short time. However, current workflows struggle to integrate critical performative analyses such as daylight availability, thermal comfort, and energy demand into the earliest phases of design.

The absence of integrated performance feedback at the stage where design decisions have the greatest impact risks overlooking important optimization opportunities. Most existing datasets for automated architectural design are limited in scope - many are synthetic rather than based on real-world buildings, which introduces a "garbage in, garbage out" risk when models are trained only on generated floorplans.

Furthermore, no publicly available datasets combine architectural layouts with geocoded information, climate data, and energy simulations, even though building performance is deeply tied to location and environmental context. This project addresses these limitations by developing a real-world architectural dataset enriched with geospatial information, environmental data, and energy simulation outputs.

Learn more: Read the full research blog post on IAAC's website

Problem Statement

AI-assisted floorplan tools prioritize speed and quantity, often neglecting performance factors like daylight and energy use. This thesis proposes a scalable workflow to enrich floorplan datasets with context-aware performance attributes, enabling more informed early-stage design and future ML applications.

Research Question

How can we create a workflow to enrich existing floorplan databases with performative data?

Credits & Acknowledgments

Research & Development

Joaquín Broquedis, Marco Durand, Matea Pinjusic
Master's Thesis Students
Institute for Advanced Architecture of Catalonia (IAAC)
Master in Advanced Computational Design for Architecture

Academic Supervision

Thesis Advisor: Angelos Chronis
Institute for Advanced Architecture of Catalonia (IAAC)

Data Sources

Building performance data and IFC models sourced from:

  • Open building performance databases
  • Collaborative research partnerships
  • Simulated building models for research purposes

Base Dataset:
Matthias Standfest, Michael Franzen, Yvonne Schröder, Luis Gonzalez Medina, Yarilo Villanueva Hernandez, Jan Hendrik Buck, Yen-Ling Tan, Milena Niedzwiecka, & Rachele Colmegna. (2022). Swiss Dwellings: A large dataset of apartment models including aggregated geolocation-based simulation results covering viewshed, natural light, traffic noise, centrality and geometric analysis (3.0.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7788422

Complete data attribution available in the Sources section.

Technical Implementation

This platform utilizes open-source technologies including:

  • Three.js: 3D model visualization
  • D3.js: Interactive graph visualizations
  • IFC.js: BIM model processing
  • Python: Data processing and analysis

Special Thanks

Gratitude to the IAAC community, fellow researchers, and the open-source software community whose tools and methodologies made this research possible.

Alexander Groth, Co-Founder and CEO of CityWeft
Jon Mirtschin, Director at Geometry Gym

How to Cite

Recommended Citation

Broquedis, J., Durand, M., & Pinjusic, M., Chronis, A. (2025). Performance Data Enriched Floorplan Dataset. Institute for Advanced Architecture of Catalonia, Master in Advanced Computational Design for Architecture, 2025

BibTeX

@dataset{iaac_performance_2025,
  title={Performance Data Enriched Floorplan Dataset},
  author={Joaquín Broquedis and Marco Durand and Matea Pinjusic},
  supervisor={Angelos Chronis},
  year={2025},
  institution={Institute for Advanced Architecture of Catalonia}
}

License

CC BY 4.0 Creative Commons Attribution 4.0 International

This dataset is freely available under Creative Commons Attribution 4.0 International License. You may use, share, and adapt the data for any purpose, including commercial use, provided you give appropriate credit to the original creators.

How to cite: Please use the citation format provided above when using this dataset in your research or projects.

Sources & References

External resources, references, and data sources used in compiling this architectural dataset.

From Building Information Modeling to Building Energy Modeling

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Buildings, 14(8), 2444

Optimization study for efficient transformation from BIM to energy modeling.

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Relational Inductive Biases, Deep Learning, and Graph Networks

Battaglia, P. W., Hamrick, J. B., Bapst, V., et al. (2018)

arXiv preprint arXiv:1806.01261

Fundamental work on graph neural networks and relational reasoning.

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Early Stage Design Decisions for Sustainable Buildings

Bragança, L., Vieira, S. M., & Andrade, J. B. (2014)

The Scientific World Journal, 2014, 365364

Achieving sustainable buildings at lower costs through early design decisions.

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ReCo: A Dataset for Residential Community Layout Planning

Chen, X., Xiong, Y., Wang, S., Wang, H., Sheng, T., Zhang, Y., & Ye, Y. (2023)

Proceedings of the 31st ACM International Conference on Multimedia

Large-scale dataset for residential community layout planning research.

View Publication →

CubiCasa5K: Annotated Floorplans Dataset

5,000 annotated floorplans with semantic labels.

Access Dataset →

Ten Questions on Urban Building Energy Modeling

Hong, T., Chen, Y., Luo, X., Luo, N., & Lee, S. H. (2020)

Building and Environment, 168, 106508

Comprehensive review of urban building energy modeling challenges and opportunities.

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Graph2Plan: Learning Floorplan Generation from Layout Graphs

Hu, R., Huang, Z., Tang, Y., van Kaick, O., Zhang, H., & Huang, H. (2020)

ACM Transactions on Graphics, 39(4), 118

Novel approach to floorplan generation using graph neural networks.

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CubiCasa5K: Dataset and Multi-task Model for Floorplan Analysis

Kalervo, A., Ylioinas, J., Häikiö, M., Karhu, A., & Kannala, J. (2019)

arXiv preprint arXiv:1904.01920

Comprehensive dataset and methodology for automated floorplan analysis.

View Publication →

Swiss Dwellings: Large Dataset of Apartment Models

Matthias Standfest, Michael Franzen, et al. (2022)

Zenodo Dataset v1.0.0

Large dataset including geolocation-based simulation results for Swiss apartment models.

Access Dataset →

AI Methodologies in Automated Floorplan Generation

Meselhy, A., & Almalkawi, A. (2025)

npj Clean Energy, 1, 2

Review of artificial intelligence approaches for high-performance floorplan generation.

View Publication →

OpenStudio – Cross-platform Tools for EnergyPlus

National Renewable Energy Laboratory (NREL) (2025)

Open-source building energy modeling tools and software platform.

Visit Website →

Building Simulations Supporting Decision Making in Early Design

Østergård, T., Jensen, R. L., & Maagaard, S. E. (2016)

Renewable and Sustainable Energy Reviews, 61, 187–201

Review of building simulation tools for early-stage architectural design.

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Urban Building Energy Modeling—A Review

Reinhart, C. F., & Cerezo Davila, C. (2016)

Building and Environment, 97, 196–202

Comprehensive review of urban building energy modeling as a nascent field.

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Building Performance Database (BPD)

U.S. Department of Energy & Lawrence Berkeley National Laboratory

Comprehensive database of building performance metrics and energy data.

Access Database →

MSD: Benchmark Dataset for Floor Plan Generation

van Engelenburg, C., Mostafavi, F., Kuhn, E., et al. (2024)

Computer Vision – ECCV 2024

Benchmark dataset for floor plan generation of building complexes.

View Publication →

ArchDaily

World's most visited architecture website.

Visit Website →

Archello

International architecture platform.

Visit Website →

OpenStreetMap

Collaborative mapping database with building and architectural data.

Visit Database →

Doors Detection in Floor Plans

Bytetrooper

Machine learning model for door detection in architectural floor plans.

View Dataset →

CityWeft: Urban Context API

Web service for urban context analysis and data.

Visit Website →

Building Types Online

De Gruyter

Comprehensive database of building types and architectural information.

Visit Database →

IDA ICE – Simulation Software

EQUA Simulation AB

Building energy simulation software for performance analysis.

Visit Website →

Energy Efficiency in Buildings

European Commission (2020)

EU focus on energy efficiency in building design and construction.

View Report →

Finch – Optimizing Architecture

AI-powered architectural optimization platform.

Visit Website →

WAFFLE: Multimodal Floorplan Understanding in the Wild

Ganon, K., Alper, M., Mikulinsky, R., & Averbuch-Elor, H. (2025)

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision

Advanced multimodal approach to floorplan analysis and understanding.

View Publication →

Hugging Face Datasets: Floorplan Masks

Repository of floorplan-related machine learning datasets.

Browse Datasets →

Evaluation of Deep Learning-based Automatic Floor Plan Analysis

Kim, H. (2021)

Applied Sciences, 11(11), 4727

AHP-based assessment of deep learning technologies for floor plan analysis.

View Publication →

Raster-to-Vector: Revisiting Floorplan Transformation

Liu, C., Wu, J., Kohli, P., & Furukawa, Y. (2017)

Proceedings of the IEEE International Conference on Computer Vision

Advanced methods for converting raster floorplans to vector representations.

View Publication →

House-GAN++: Generative Adversarial Layout Refinement

Nauata, N., Hosseini, S., Chang, K.-H., Chu, H., Cheng, C.-Y., & Furukawa, Y. (2021)

IEEE/CVF Conference on Computer Vision and Pattern Recognition

Advanced generative model for professional architectural layout design.

View Publication →

Nextroom

Austrian architecture database and platform.

Visit Website →

InvSR: Image Enhancement and Super-resolution

OAOA

Web application for image enhancement and super-resolution processing.

Try Application →

Switzerland Energy Efficiency Profile

ODYSSEE-MURE (2025)

Comprehensive analysis of energy efficiency trends and policies in Switzerland.

View Report →

PineTools: Invert Image Colors

Web tool for image color inversion and processing.

Try Tool →

HouseDiffusion: Vector Floorplan Generation via Diffusion Model

Shabani, M. A., Hosseini, S., & Furukawa, Y. (2023)

IEEE/CVF Conference on Computer Vision and Pattern Recognition

Novel diffusion model approach for vector floorplan generation.

View Publication →

EnergyPlus Essentials

U.S. Department of Energy (2024)

Version 24.1.0

Comprehensive guide to EnergyPlus building energy simulation software.

View Documentation →

Machine Learning as Surrogate Model for Heating-Demand Optimization

Wang, X., Harrison, J., Teigland, R., & Hollberg, A. (2024)

Proceedings of SimBuild 2024 (IBPSA-USA)

ML approaches for early-stage heating demand optimization in buildings.

View Publication →

Automated Floorplan Generation in Architectural Design

Weber, R. E., Mueller, C., & Reinhart, C. F. (2022)

Automation in Construction, 140, 104385

Comprehensive review of methods and applications for automated floorplan generation.

View Publication →

Vectorizer AI: Raster to SVG

Weepakistan

Web application for converting raster images to vector SVG format.

Try Application →

Surrogate Modelling for Sustainable Building Design

Westermann, P., & Evins, R. (2019)

Energy and Buildings, 198, 170–186

Comprehensive review of surrogate modeling approaches in sustainable building design.

View Publication →

Köppen Climate Classification

Wikipedia contributors

Comprehensive information on Köppen climate classification system.

View Article →

Bringing Embodied Carbon Upfront

World Green Building Council (2019)

Report on embodied carbon in building construction and design.

View Report →

Pseudo Floor Plan 12k Dataset

zimhe

Large dataset of pseudo floor plan images for machine learning research.

Access Dataset →