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.


Designing, communicating, and programming a user interface: SeisNAV

The first three exercises focused on designing and coding a landing page, visualizing geospatial data on Mapbox, and creating an interactive 3D experience with Three.js, each progressively building skills in design, data integration, and interactivity to address real-world challenges. ⠀ SeisNAV – User interfaces This project involved designing user interfaces for SeisNAV with a focus … Read more

Green Liminals : Dashboard Interface for Feasibility Study | AI-Driven Budget Optimization Tool  for Urban Sustainable Solutions

Abstract The project explores innovative ways to address Barcelona’s sustainability challenges, such as carbon emissions, air pollution, and energy inefficiency.By leveraging AI, IoT sensors, and Nature-Based Solutions (NBS), the project aims to optimize municipal budgets for interventions that transform underutilized urban spaces into productive assets. The study highlights solutions like urban farming, greenery, and solar catchment systems, evaluated … Read more

SeisNAV

Abstract: Natural disasters, especially earthquakes, often leave roads blocked, buildings collapsed, and maps outdated, making navigation and response efforts highly challenging, That’s where we operate. Our project SeisNAV is an AI-powered platform that combines satellite imagery and computer vision to detect collapsed structures and road blockages, providing real-time mapping and navigation tools for disaster response … Read more

Green Liminals: Feasibility Study for AI-Driven Budget Optimization for Urban Sustainable Solutions

Abstract The project explores innovative ways to address Barcelona’s sustainability challenges, such as carbon emissions, air pollution, and energy inefficiency. By leveraging AI, IoT sensors, and Nature-Based Solutions (NBS), the project aims to optimize municipal budgets for interventions that transform underutilized urban spaces into productive assets. The study highlights solutions like urban farming, greenery, and … Read more