• Gauri Khandezod
• Sonal Jadhav
• Sanjaykumar Ranveer

Augmented Reality (AR) and Machine Learning (ML) are transforming interior design by enhancing visualization, reducing costs, and streamlining planning. Traditional methods involve manual sketches, expert consultations, and trial-and-error approaches, making the process time-consuming and expensive. Homeowners and designers often struggle to visualize furniture placement and décor before making modifications, leading to uncertainty and inefficiencies. This research integrates AR and ML to develop an interactive, real-time interior design tool. AR enables users to place virtual furniture within real-world spaces, providing a realistic and immersive design experience. Meanwhile, ML algorithms analyze user preferences, spatial constraints, and design trends to offer personalized recommendations. This combination minimizes guesswork, optimizes layouts, and improves decision-making efficiency. Key features include AI-driven automation, 3D scanning for precise room mapping, and real-time collaboration between designers, homeowners, and architects. However, challenges such as hardware limitations, data privacy concerns, and computational demands must be addressed for broader adoption. As AR and ML technologies continue to advance, their integration into interior design will become more accessible, scalable, and intelligent. This research explores a technology-driven approach to making interior design more interactive, efficient, and user-friendly.

" Enhancing Interior Design Through Augmented Reality and Machine Learning Integration", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 5, page no.c272-c275, May-2025, Available :http://www.jetir.org/papers/JETIR2505234.pdf

" Enhancing Interior Design Through Augmented Reality and Machine Learning Integration", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 5, page no. ppc272-c275, May-2025, Available at : http://www.jetir.org/papers/JETIR2505234.pdf