AI applied to architecture
The RoVIT Research Group explores how Artificial Intelligence can revolutionize architecture by supporting design, analysis, and management of built environments. Our research focuses on leveraging AI to optimize efficiency, sustainability, and creativity in architectural processes, bridging the gap between human expertise and computational intelligence.
Research Objectives
Structural and Energy Analysis
Apply machine learning to predict performance, reduce energy consumption, and improve building resilience.
Building Information Modeling (BIM)
Enhance BIM with AI to support automated classification, error detection, and data-driven decision-making.
Smart Cities and Environments
Integrate AI into urban planning and infrastructure management to improve livability and sustainability.
Heritage and Restoration
Employ AI-based methods for documenting, analyzing, and preserving historical architecture.
Technologies We Use
Generative AI and deep learning for design exploration.
Computer vision for architectural image analysis, defect detection, and 3D reconstruction.
Knowledge-based systems for automated compliance with building codes and regulations.
Reinforcement learning for adaptive energy and resource management.
Digital twins for simulation and real-time monitoring of built environments.
Applications
Impact
Our work in AI applied to architecture contributes to building smarter, greener, and more adaptive environments. By combining artificial intelligence with architectural knowledge, we aim to support professionals in creating sustainable spaces, improving resource efficiency, and enhancing the human experience in built environments.
