| Title: | The use of artificial intelligence in building engineering for historic buildings build in the Austro-Hungarian monarchy |
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| Authors: | ID Dvornik Perhavec, Daniela (Author)
ID Kamnik, Rok (Author) |
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| Files: |  3706424.pdf (6,35 MB)
MD5: 36750C99E0C90B8EDB512CCA0EFA3BF1
 https://dl.acm.org/doi/10.1145/3706424
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| Language: | English |
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| Work type: | Article |
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| Typology: | 1.01 - Original Scientific Article |
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| Organization: | FGPA - Faculty of Civil Engineering, Transportation Engineering and Architecture
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| Abstract: | Knowledge discovery from databases (KDD) and data mining (DM) belong to the field of artificial intelligence (AI). The integration of artificial intelligence into various segments of the construction industry is still in its infancy, but it is expected to be used more widely soon, driven by the development of databases and data warehouses. By using BIM (Building Information Modelling) technologies in the planning of new buildings, we will be able to obtain valuable data. The situation is different for old, existing buildings and the building engineering associated with these properties. Civil engineers, renovation planners and architects need knowledge of the building before renovation. This knowledge is much less than the possibilities that exist. Information about the building can be found in provincial archives. For historic buildings, 10- 15% of the plans, drawings, descriptions, or projects are available. The remaining 85% must be researched on site, which is a lengthy and costly process and hinders the construction process. The question arose as to how the findings from the study of buildings based on written and preserved sources can be applied to the 85% of buildings for which no data is available. This paper presents the use of the collected data as an idea for an initiative to develop a database and modelling using artificial intelligence algorithms. The research study investigates the feature “load-bearing wall” for residential buildings with basements and floors built between 1857 and 1948 in the former Austro-Hungarian Empire. The aim of this study is to create a model to predict the characteristics of a building for which no archival material is available. The study is based on the use of artificial intelligence in the creation of decision trees to help engineers improve their knowledge of historic buildings in the former Austro-Hungarian Empire and building engineering for historic objects. |
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| Keywords: | knowledge discovery from data, machine learning, Austro-Hungarian Monarchy buildings |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Submitted for review: | 07.02.2024 |
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| Article acceptance date: | 03.11.2024 |
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| Publication date: | 17.02.2025 |
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| Publisher: | Association for Computing Machinery |
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| Year of publishing: | 2025 |
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| Number of pages: | [21] str. |
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| PID: | 20.500.12556/DKUM-91927  |
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| UDC: | 930.85:004.8 |
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| ISSN on article: | 1556-4711 |
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| COBISS.SI-ID: | 220404995 |
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| DOI: | 10.1145/3706424 |
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| Copyright: | ©2025 Copyright held by the owner/author(s). |
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| Publication date in DKUM: | 03.03.2025 |
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| Views: | 137 |
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| Downloads: | 9 |
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| Metadata: |    |
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| Categories: | Misc.
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