Automated Classification of Building Objects using Machine Learning

Nadeem Iftikhar, Peter Nørkjær Gade, Kasper Møller Nielsen, Jesper Mellergaard

Research output: Chapter in Book/Report/Conference proceedingConference contribution to proceedingpeer-review


In the construction sector, digital technologies are being employed to enable architects, engineers and builders in the creation of digital building models. Although these technologies come equipped with inherent classification systems, they also bring forth certain obstacles. Frequently, these systems categorize building elements at levels that exceed their necessary specificity. To illustrate, these classification systems might allocate values at a broader granularity, such as “exterior wall” rather than at a more precise level, like “exterior glass wall with no columns”. As a result, the manual classification of building elements at a granular level becomes essential. Nonetheless, manual classification frequently results in inaccuracies and erroneous semantic details, while also consuming a significant amount of time. Precise and prompt classification of building objects holds significant importance for activities like cost planning, construction cost management and overall procurement processes. To address this, the current paper suggests an automated classification approach for building objects, focusing on specific types, through the utilization of machine learning. The effectiveness of the proposed system is showcased using real-world data from a prominent architectural firm based in Scandinavia.
Original languageEnglish
Title of host publicationProceedings of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2023
EditorsAna Fred, Frans Coenen, Jorge Bernardino
Number of pages8
PublisherSCITEPRESS Digital Library
Publication date2023
ISBN (Electronic)978-989-758-671-2
Publication statusPublished - 2023
Event15th International Conference on Knowledge Discovery and Information Retrieval - Rome, Italy
Duration: 13 Nov 202315 Nov 2023


Conference15th International Conference on Knowledge Discovery and Information Retrieval
OtherKnowledge Discovery (KD) is an interdisciplinary domain focusing upon methodologies for identifying valid, hidden, novel, potentially useful and meaningful information from within data of all kinds. Knowledge discovery encompasses an end-to-end process ...
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