This project aims to develop an AI system that predicts client preferences in interior design based on inputs such as lifestyle, budget, and aesthetic choices. The system will assist designers in creating personalized, efficient, and client-centric design solutions using data-driven insights.
Study how interior designers gather and interpret client requirements in real-world projects.
Identify key factors influencing design decisions such as lifestyle, family size, budget, and aesthetic preferences.
Collect and prepare datasets including design styles, client profiles, and completed project case studies (can include anonymized real data).
Preprocess and categorize data into meaningful groups such as modern, minimalist, traditional, etc.
Develop machine learning models (e.g., classification or recommendation systems) to predict suitable design styles and layouts.
Design a user interface where clients input their preferences, needs, and constraints.
Generate AI-based design suggestions including style recommendations, color themes, and furniture types.
Compare AI-generated suggestions with actual design decisions from real projects.
Evaluate system accuracy, relevance, and user satisfaction.
Optimize the model to improve personalization and adaptability.
Document findings with real-life case studies to demonstrate how AI enhances client-designer collaboration.
