Smart Interior Design System Leveraging ML and Augmented Reality for Personalization

Interior design has conventionally relied on the expertise of designers and subjective client preferences to achieve aesthetically pleasing and functional spaces. Recent advancements in technology particularly Machine Learning (ML) and Augmented Reality (AR) have introduced new opportunities for enhancing personalization in interior design. This study proposes a smart interior design system that integrates ML and AR to deliver highly tailored design solutions aligned with individual user preferences and spatial requirements. The primary objective is to assess the impact of ML and AR on user satisfaction, space optimization, and aesthetic appeal in personalized interior environments. A quantitative research method was employed, utilizing user feedback surveys and interactions with an AR-based interior design prototype. ML algorithms were applied to analyze user input and predict optimal design configurations, while AR technology enabled users to visualize and interact with real-time design adjustments. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to examine relationships among key variables. Findings reveal that both ML and AR significantly contribute to enhanced user satisfaction. AR plays a prominent role in improving perceived aesthetic appeal, while ML demonstrates a strong effect on optimizing spatial arrangements. Moreover, the combined use of ML and AR produces a synergistic effect, resulting in a more immersive and user-centric design experience. The study concludes that integrating intelligent technologies into the interior design process leads to functionally efficient and visually appealing spaces, thereby advancing the personalization of design practices. Future work may explore the incorporation of virtual reality to further expand adaptive design capabilities.