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.
(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
This project focuses on Evia, Greece, where devastating wildfires in the summers of 2021 and 2023 caused massive environmental damage. This is only an example, but this pipeline could be applied to any wild-fire affected area. Our aim is to quantify green loss and monitor post-fire ecosystem recovery. Thus we compare satellite imagery from key … Read more
The project is situated in Athens, Greece, which overheats in the summer. We wanted to test a hypothesis: The overheating is the result of too much hardscaping (asphalt, concrete, brick) and not enough greenery. We wanted to compare the NDVI (a measure of greenery in a city) taken from Satellite images to Land Surface Temperature … Read more
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
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
