Neuro-symbolic approach for querying BIM models - Archive ouverte HAL
Communication Dans Un Congrès Année : 2024

Neuro-symbolic approach for querying BIM models

Approche neuro-symbolique pour requêter les modèles BIM

Anthony Dumas
  • Fonction : Auteur
  • PersonId : 1321428
Roxin Ana

Résumé

Integrating technologies like the Internet of Things (IoT) and artificial intelligence (AI) has transformed the smart building domain, enabling innovative services. The data gathered throughout a building's lifecycle, including construction and usage, create a comprehensive database for efficient management and improvement, mainly through Building Information Modelling (BIM). However, accessing and utilising these data can be challenging for users, as it often requires specialised query skills. Improving information accessibility involves intuitive and user-friendly query interfaces. Traditional approaches struggle to provide the flexibility and adaptability needed to keep up with evolving building information and user language expressions. To address these challenges, modern and scalable methods from symbolic and numeric artificial intelligence offer a solution. These systems can handle varying queries, adapt to changing data, and provide more user-friendly interactions, aligning better with user expectations in the industry.
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Dates et versions

hal-04353150 , version 1 (19-12-2023)

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Copyright (Tous droits réservés)

Identifiants

Citer

Stéphane Reynaud, Anthony Dumas, Roxin Ana. Neuro-symbolic approach for querying BIM models. 17th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS), Nov 2023, Bangkok, Thailand. pp.62-69, ⟨10.1109/SITIS61268.2023.00019⟩. ⟨hal-04353150⟩
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