Innovative Design Synthesis: AI-Driven Solutions for Sustainable Urban Planning: Development, Evaluation, and Insights

Abstract

This research aims to explore the capabilities of Artificial Intelligence model applications in sustainable urban planning design, aiming to create an AI-powered model that detects urban sprawl, urban decay, infrastructure deficiencies, and environmental degradation, and generates sustainable solutions. The methodology includes model development, data preprocessing, architecture design, training, and comprehensive questionnaire design and statistical analysis. Insights into the model's performance and perception were gathered from 200 participants, including researchers, developers, architects, and urbanists Results reveal significant variations in perceived model performance across demographic groups. Statistical tests and correlations study showed that participants from urban areas rated the model's effectiveness in detecting urban sprawl significantly higher than those from rural areas, and urban planners found the model's infrastructure deficiency detection less accurate compared to architects. These findings provide valuable guidance for enhancing urban planning strategies and underscore AI's potential in transforming urban planning with more effective and inclusive solutions.

Keywords

• Artificial Intelligence
• Sustainable Urban Planning
• Model Development
• Urban Problems Detection