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.


Urban Vegetation Analysis Using Computer Vision and Deep Learning

(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

Agrowealth : Does agriculture correlate to economy?

The goal of this project is to compare between the economic stability of an agriculture first city. Hamburg’s agricultural wealth is largely connected to its surrounding regions—particularly Schleswig-Holstein and Lower Saxony, which are among Germany’s leading food producers. Consequently, we focused on peripheral areas of the city that have recently transitioned into agricultural land, allowing … Read more

AI For Robotic Fabrication Workshop : Reinforcement Learning for Intelligent Grid-Based Carving

Can an AI agent learn how to carve a shape — not by following a predefined path, but by figuring it out on its own? https://github.com/IaaC/AI_Robotics_Octopus.git Inspired by the precision of traditional craftsmanship, especially techniques like Japanese joinery where every cut matters, we wanted to see if a machine could learn that same logic in … 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

Green Enough? Assessing Barcelona’s Compliance with EEA Green Space Standards Per Capita Using Geospatial Analysis.

AbstractGreen spaces play a critical role in enhancing urban livability by improving air quality, reducing urban heat island effects, and promoting mental and physical well-being.This project evaluates the spatial distribution of green spaces in Barcelona and their compliance with the European Environment Agency (EEA) standard of 9 m² of green space per person. By overlaying … Read more