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Master in AI for Architecture and the Built Environment

IAAC’s Master in AI for Architecture & the Built Environment is a unique program oriented towards leading the change in decarbonising human activities and crafting a more sustainable, resilient future urbanisation for our planet. Through an innovative curriculum deeply rooted in AI applications, the program pioneers novel AI-driven solutions that not only respond to the pressing challenges of our time but also set a new standard for environmentally and socially conscious co-design and planning. The Master in AI for Architecture & the Built Environment is training the professionals that city administrations, governments, industries, and communities need, to transform the built environment in the era of digital technologies.


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CINEFLOW : An AI-Powered Cinematic Walkthrough for Architectural Design


MaAI-01 2024-2025 by
MaAI-01 2024-2025

Automating Architectural Visualization: A Journey Through Technical Pivots and AI Evolution Introduction In the rapidly evolving landscape of architectural visualization, the gap between conceptual design and compelling visual presentation remains a significant challenge. While architects and designers excel at creating innovative spaces, transforming these 3D models into cinematic walkthroughs typically requires specialized skills, expensive software, … Read more

Interactive Block-Based Structural Generation and Analysis Tool


MaAI-01 2024-2025 by
MaAI-01 2024-2025

In contemporary architectural practice, the gap between conceptual design and structural analysis often leads to delays, miscommunication, and inefficient iteration cycles. This project proposes an integrated workflow that bridges this divide by creating an interactive interface where architects can receive real-time structural feedback while scanning their preliminary physical model. By combining Unity-based visualization, QR code-enabled … Read more

Urban Vegetation Analysis Using Computer Vision and Deep Learning


MaAI 2024-2025 by
MaAI 2024-2025

(PaintDumpster/environmental_data_workshop at ndvi) – Link to GitHub This project aims to detect and classify different types of greenery in satellite imagery by utilizing color and edge detection techniques. The study area is located in Barcelona, Spain (41.396536, 2.194554). The stable version employs color and edge detection for image segmentation, while an alternative method integrates LiDAR … Read more

Flood Impact Mapping along the Turia River, València – Flood of 2024


MaAI-01 2024-2025 by
MaAI-01 2024-2025

When torrential rain dumped an entire year’s worth of water on Valencia in barely eight hours on 29 October 2024, the Turia spilled over its banks, submerging citrus groves, highways and whole neighbourhoods. More than 200 lives were lost, hundreds remained missing and Spain faced its worst flood disaster in recent history. Events like this … Read more