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ORIGINAL RESEARCH article
Front. Built Environ.
Sec. Indoor Environment
Volume 10 - 2024 |
doi: 10.3389/fbuil.2024.1413153
The Application of Machine Learning in Inner Built Environment: Scientometric Analysis, limitations, and Future Directions
Provisionally accepted- Department of Interior Design, Faculty of Architecture and Design, Middle East University, Amman, Amman, Jordan
This article investigates the revolutionary influence of artificial intelligence (AI) on interior design, with an emphasis on the incorporation of machine learning ML techniques. The advent of AI has resulted in a paradigm change in design methods, prompting a thorough review of research gaps and the potential for ML applications in a variety of areas of interior design. A systematic review process was implemented to fill these gaps, consisting of an in-depth evaluation of 28 research publications from Scopus databases categorized into eight themes. The investigation sought to address a pair of primary inquiries: what opportunities exist for using ML in interior design conditions, and what challenges limit its effective implementation. The study discovered a significant gap in the existing literature, demanding a full assessment to highlight challenges in ML implementation and the potential for applied ML development throughout the whole spectrum of interior design. The findings are intended to provide researchers and enthusiasts with an extensive understanding of ML-based gaps in interior design conditions and to provide various solutions for filling these gaps. This understanding may assist in the development of intelligent ML-driven apps, promoting interior contexts that improve user well-being and psychological comfort.
Keywords: machine learning, Interior Design, artificial intelligence, Interior-Environment, Smart technology, sustainability
Received: 06 Apr 2024; Accepted: 31 Oct 2024.
Copyright: © 2024 Albast and Aldweik. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Safaa M. Albast, Department of Interior Design, Faculty of Architecture and Design, Middle East University, Amman, Amman, Jordan
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.