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
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
Tracking Morphological Evolution Over Time Urbanization and Vegetation Change Analysis Using Satellite Data Introduction Satellite imagery provides a powerful view of Earth’s surface, but to the naked eye, changes like urban growth and vegetation loss are not always obvious over time.Colors and features can look deceptively similar, making it difficult to accurately assess land cover … Read more
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
The work presented in this blog post explores how code and visual tools can be used to create and represent the data central to this research group’s main project in the Research Studio. It focuses on integrating data-driven design methods to support sustainable façade development while aligning with environmental guidelines. By emphasizing the creation and … Read more
