The Master in City & Technology’s academic structure is based on IAAC’s innovative, learn-by-doing and design-through-research methodology which focuses on the development of interdisciplinary skills. During the Master in City & Technology students will have the opportunity to be part of a highly international group, including faculty members, researchers, and lecturers, in which they are encouraged to develop collective decision-making processes and materialize their project ideas.
As part of a collaborative exploration into creative automation and human-AI interaction, our team developed an AI-powered weather assistant that integrates live data, generative visuals, and contextual language processing into a single, responsive system. The assistant operates via a Telegram bot and delivers three core outputs: current weather information, clothing recommendations, and an AI-generated image … Read more
A speculative approach to Design through data, literature, and participatory AI in Sant Antoni Our urban issue: The Lack of Narrative-Driven Urban Design in a Data-Driven City Contemporary urban design increasingly relies on AI and big data, often sidelining human stories, cultural narratives, and historical context in shaping urban spaces. While data-driven design optimizes efficiency, … Read more
An alternative ways of exploring the sounds that make up Gràcia This project investigates alternative ways of engaging with the sounds of Gràcia and how they can empower communities by fostering a deeper connection to place, memory, and identity. Sound functions as both a sensory experience and a cultural artifact, carrying layers of emotion, history, … Read more
We live in an age of constant information, where news spreads rapidly and surrounds us at all times. Social media notifications, breaking news alerts, and endless headlines create an overwhelming cycle. Unfortunately, negativity often dominates this flow, increasing stress, anxiety, and emotional fatigue. Why Are People Avoiding the News? According to Universitat Oberta de Catalunya, … Read more
Designing an Inclusive and Functional Bench Through the Lens of Iconic Visionaries Urban design has always required balancing complex social, cultural, and environmental factors. In this project, we explored the potential of AI in shaping public spaces. Specifically, designing a bench that serves the needs of both homeless individuals and daily users. We developed a … Read more
Barcelona, like many modern cities, experiences the Urban Heat Island (UHI) effect, where built-up areas retain more heat than surrounding natural landscapes. This interactive map visualizes temperature variations across the city, highlighting areas most affected by heat buildup. 🛰️ What This Map Shows: 📍 Heat Hotspots – Areas with high surface temperatures due to dense construction and limited … Read more
The project started with an experiment to see if an agent could follow a line and illuminate its path to see obstacles. The light is composed of isovits and only the ones in front of the agent are colored. The experiment went then to make the light 3D to illuminate buildings facades. Many approaches were … Read more
The persistent expansion of urbanization poses a significant threat to wildlife populations. One under-explored facet of this impact concerns the genetic health of these populations. Genetic diversity, measured by the variation within a gene pool, is crucial for resilience and adaptation. This project utilizes Grashopper-led simulations to explore the dynamics between habitat fragmentation, animal movement, … Read more
Based on the theoretical frameworks of diverse urban theorists, this project explored multiple dynamics between the metropolis, design, and technology within the context of the Anthropocene epoch and the rise of technology. The following lexicon was developed and graphically illustrated with the assistance of Artificial Intelligence, creating images that aim to cause a cognitive effect … Read more
Mazes have fascinated humans for centuries. Solving them requires decision making based on limited knowledge, and the ability to remember and avoid previous mistakes. The problem of solving a maze from any given position within it, without knowing the location of the exit lends itself well to the iterative logic that is central to this … Read more
Black Holes | Black holes accumulate mass with such force that light cannot escape. The invisible hand drove technological innovation resulting in economies of scale to production. This allowed for flexibility in the accumulation of capital and its products, compressing relative time and space, giving way to increasingly accessible and ephemeral consumption of goods, services, … Read more
The project focuses on promoting the physical, mental, and social well-being of older adults in the city of Barcelona through various initiatives, the goal is to empower older adults to remain active and engaged in their communities, and to promote healthy ageing and independence. Projected population aged 65+ What is Ageing? Health in the older … Read more
The New York City Taxi Trip Duration competition is a challenge to develop a model that predicts the total ride time of taxi trips in New York City. Yellow medallion taxicabs, which number 12,779 in New York City, generate a substantial revenue of $1.8 billion per year by providing transportation services to around 240 million … Read more
Goal: to predict trip duration of NYC cabs using machine learning models. Tools: Python + Nympy + Pandas + Datetime + Plotly.express + Matplotlib + Math + Seaborn + Bokeh + Sklearn Stages of project: data cleaning, data analysis, data preparation, data testing, evaluating prediction accuracy. Data cleaning The first dataset visualization with splitting datasets … Read more
Machine Learning-based Analysis of NYC Cab Trip Duration “Data-Driven Rides” is an entry for the first MaCT Machine Learning Competition that hosted on Kaggle which involves predicting the duration of taxi rides in New York City. The dataset provided for this competition is based on the 2016 NYC Yellow Cab trip record dataset and the … Read more
The MaCT01 students were tasked with training a model that would be used to predict NYC yellow taxi ride durations using machine learning. The dataset included pickup and drop-off datetimes, location coordinates and passenger count. Visualizing the data helped to understand the correlation between the columns and remove the highly correlated values Understanding the distribution … Read more
