The application of machine learning in inner built environment: scientometric analysis, limitations, and future directions

Introduction

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.

Methods

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.

Result

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.

Discussion

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.