Go Back

Master in AI for Architecture and the Built Environment 01

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.

Filtered (4)
Filters
Years
Term
Course
Tag
Show (4)
Cancel

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

by
MaAI-01 2024-2025

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

Intelligent Prototyping: robotics and micro-controllers

by
MaAI-01 2024-2025

The work presented in this blog post is an approach combining Robotics and Microcontrollers as preparation for a main Research Studio project focused on sustainable facades and environmental guidelines. This represents our first steps in exploring these fields and their connections with Artificial Intelligence in Architecture and the Built Environment. In the Robotics domain, the … Read more

AI theory: Using NLP – Graph Rag for AI Suggestions in Facades, based on environmental guidelines

by
MaAI-01 2024-2025

This project leverages Graph Retrieval-Augmented Generation (Graph RAG) to provide intelligent facades configuration recommendations aligned with the New European Bauhaus (NEB) principles. This post presents how we apply AI theory approaches for reaching the stablished target. The project correlates quantitative data and qualitative guidelines, by integrating 17% of the assessed metrics in this guidelines and creating … Read more