Communication Dans Un Congrès Année : 2024

Scan-to-BIM: Unlocking current limitations through Artificial Intelligence

Résumé

Building Information Modeling (BIM) is crucial for the digital transformation in the Architecture, Engineering, and Construction (AEC) industries. However, implementing BIM for existing buildings presents significant challenges. The Scan-to-BIM process addresses these challenges by converting real-world data into BIM-ready formats using advanced technologies like laser scanning and photogrammetry. This poster explores how Artificial Intelligence (AI) enhances the Scan-to-BIM workflow, improving efficiency and accuracy.

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Dates et versions

hal-04603859 , version 1 (06-06-2024)

Identifiants

  • HAL Id : hal-04603859 , version 1

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Maxime Queruel, Stefan Bornhofen, Aymeric Histace, Laure Ducoulombier. Scan-to-BIM: Unlocking current limitations through Artificial Intelligence. The 41st International Symposium on Automation and Robotics in Construction, Jun 2024, Lille, France. ⟨hal-04603859⟩
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