Logo Oapen
  • Search
  • Join
    • Deposit
    • For Librarians
    • For Publishers
    • For Researchers
    • Funders
    • Resources
    • OAPEN
    • For Librarians
    • For Publishers
    • For Researchers
    • Funders
    • Resources
    • OAPEN
    View Item 
    •   OAPEN Home
    • View Item
    •   OAPEN Home
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Chapter Transforming Building Industry Knowledge Management: A Study on the Role of Large Language Models in Fire Safety Planning

    Thumbnail
    Download PDF Viewer
    Web Shop
    Author(s)
    Ashkenazi, Ori
    Isaac, Shabtai
    Giretti, Alberto
    Carbonari, Alessandro
    Durmus, Dilan
    Language
    English
    Show full item record
    Abstract
    This paper discusses the potential use of AI in general, and large language models (LLMs) in particular, to support knowledge management (KM) in the building industry. The application of conventional methods and tools for KM in the building industry is currently limited due to the large variability of buildings, and the industry’s fragmentation. Instead, relatively labor-intensive methods need to be employed to curate the knowledge gained in previous projects and make it accessible for use in future projects. The recent development of LLMs has the potential to develop new approaches to KM in the building industry. These may include querying a variety of relatively unstructured documents from previous projects and other textual sources of technical expertise, processing these data to create knowledge, identifying patterns, and storing knowledge for future use. A proposed framework is defined for the use of LLMs for KM in construction. We will perform preliminary analyses on how to train models that can generate information and knowledge required to make decisions in the development of specific tasks of fire safety planning
    URI
    https://library.oapen.org/handle/20.500.12657/89059
    Keywords
    Large Language Models (LLMs); Knowledge Management (KM); Fire Safety Planning; Expert Systems (ESs); Artificial Intelligence (AI); Knowledge Graph; Ontology
    DOI
    10.36253/979-12-215-0289-3.73
    ISBN
    9791221502893, 9791221502893
    Publisher
    Firenze University Press
    Publisher website
    https://www.fupress.com/
    Publication date and place
    Florence, 2023
    Series
    Proceedings e report, 137
    Classification
    Linguistics
    Literature: history and criticism
    Pages
    10
    Rights
    https://creativecommons.org/licenses/by-nc/4.0/legalcode
    • Imported or submitted locally

    Browse

    All of OAPENSubjectsPublishersLanguagesCollections

    My Account

    LoginRegister

    Export

    Repository metadata
    Logo Oapen
    • For Librarians
    • For Publishers
    • For Researchers
    • Funders
    • Resources
    • OAPEN

    Newsletter

    • Subscribe to our newsletter
    • view our news archive

    Follow us on

    License

    • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

    Credits

    • logo EU
    • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

    OAPEN is based in the Netherlands, with its registered office in the National Library in The Hague.

    Director: Niels Stern

    Address:
    OAPEN Foundation
    Prins Willem-Alexanderhof 5
    2595 BE The Hague
    Postal address:
    OAPEN Foundation
    P.O. Box 90407
    2509 LK The Hague

    Websites:
    OAPEN Home: www.oapen.org
    OAPEN Library: library.oapen.org
    DOAB: www.doabooks.org

     

     

    Export search results

    The export option will allow you to export the current search results of the entered query to a file. Differen formats are available for download. To export the items, click on the button corresponding with the preferred download format.

    A logged-in user can export up to 15000 items. If you're not logged in, you can export no more than 500 items.

    To select a subset of the search results, click "Selective Export" button and make a selection of the items you want to export. The amount of items that can be exported at once is similarly restricted as the full export.

    After making a selection, click one of the export format buttons. The amount of items that will be exported is indicated in the bubble next to export format.