Within the current global context of rapid change, integrated with the potentials of digital technologies, IAAC’s Master in AI for Architecture and the built environement (MaAI01) is committed to the generation of new ideas and pioneer novel AI-driven solutions applications for the fields of Urban Tech, Smart Construction and Natural Ecosystems. The three transversal objectives of the program are Regenerative Design, Carbon Neutrality and Co-Design Processes.
In this context IAAC and the MaAI works with a multidisciplinary approach, integrating computational design, rapid prototyping, machine learning, data science, and generative AI implementing sustainable practices at an unprecedented scale. Facing the challenges posed by our environment and the future development of cities, architecture and buildings, through a virtuous combination of technology, biology, computational design, digital and robotic fabrication, pushing innovation beyond the boundaries of a more traditional architectural approach.
The course informs the students about the constantly evolving technological landscape and provide them with the instruments allowing one to evaluate different technologies and apply them to solve the problems within the industry. Moreover, this course gives a broader perspective on data and machine learning pipelines enabling the students to interact with data specialists using correct terminology and understanding the implications of project decisions.
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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
