AI-Based Predictive Model for Interior Design

Interior design projects involve complex planning processes that include budgeting, material selection, labor management, and project scheduling. Traditional estimation methods often rely on manual calculations and personal experience, which may lead to inaccurate cost predictions and project delays. With the advancement of Artificial Intelligence (AI), predictive models can analyze historical data and provide accurate forecasting for future projects. This project focuses on developing an AI-based predictive model that can estimate project costs and timelines for interior design projects. The model uses historical project data such as project size, material costs, labor costs, and design complexity to identify patterns and generate predictions. The proposed system aims to assist interior designers and project managers in improving planning accuracy, reducing cost overruns, and enhancing project management efficiency. The results of the study demonstrate how AI-driven predictive analysis can improve decision-making in the interior design industry. The project highlights the importance of integrating modern technologies to optimize budgeting, resource allocation, and project scheduling