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eSketch: A Multimodal Generative AI Design Interface and Human-Centered Approach for a Neural Design Phase

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Research Team

Our Motivation:

"Current Generative Artificial Intelligence (GenAI) methodologies are not capable of generating Building Information Models (BIMs) directly. This limitation can hinder their effectiveness in providing comprehensive insights for informed investments in GenAI"


 

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Research Contribution

Addressing the question of whether these GenAI methods enhance design skills, our research aims to develop eSketch, a design interface seamlessly integrated with GenAI techniques and human-centered approaches. 

The primary goal of this development is to evaluate the overall user experience and its correlation with design skills. To achieve this, we will conduct comparative user studies, comparing the performance of our methods with established benchmarks. 

For instance, we will assess how eSketch users' design skills compare to those using traditional design tools and workflows.

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Problem

Practical Problem

In the context of Industrialized Construction (IC), the early-stage designs frequently lack essential constructability insights. This deficiency results in delays, as modular construction companies invest weeks in the process of modifying designs to align with their specific building modules and construction methodologies. Consequently, latency emerges between the schematic design phase and the development stages.

Conceptual Problem

The absence of a user-friendly interface capable of facilitating real-time constructability assessments while utilizing preferred early-stage design tools, such as sketches, diagrams, inspirational images, text, or speech, impedes the seamless integration of essential practical building considerations.

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Solution

The solution consists in the development of an interface for evaluating the GenAI methodology in the context of Industrialized Construction (IC) project design.

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Added Value For The Industry

It will empower industry partners to generate Building Information Models (BIM) from initial design concepts, thereby reducing the time lag between the schematic and development phases within the Industrialized Construction framework.

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Cooperation Partner

GOLDBECK, German
NVIDIA Corporation, USA
NVIDIA Corporation, USA
Amazon Web Service, USA

 

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 Timeline

DateActivityOutcome

October 2023

Research became awarded

 

April 2024

Finalize an initial working deep generative model

 

June 2024

Initial Prototype

 

Summer 2024

Initial User Interface Studies

 

If you want to participate in the project please reach out to Alberto Tono.