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.

From following instructions to autonomy

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

Urbanization and gene pools: A simulation study

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

Redefining the Urban

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

Solving the maze

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 and Revelations’

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

Active Ageing in Barcelona

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

NYC Taxi Time Traveler

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

Machine learning model to predict NYC cabs’ trip duration

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

Data-Driven Rides

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

Predicting NYC Cab Ride Duration using ML

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

2016 NYC Yellow Cab trip

The source dataset provided for this project is derived from the 2016 NYC Yellow Cab trip records, which were made publicly available on the Big Query platform of the Google Cloud. The data was originally collected and published by the New York City Taxi and Limousine Commission (TLC). This dataset serves as the foundation for … Read more

1st Traditional IAAC MaCT ML Competition

#Objective #A Kaggle Competition to MaCT01 students to show their knowledge, designing an end-to-end machine learning project to predict the “Trip Duration” of NYC Taxi trips. #Workflow #First of all a workflow hast do be developed, which represents a classic approach for training machine learning models, analysing the provided training data provided by the submission, … Read more

NYC Cab Trip Duration Prediction

The aim of the project is to predict trip duration, using 2016 NYC YELLOW CAB TRIP DATA. Structuring the dataset The analysis begins with outlier identification. The passenger_count variable has two outliers: 0 and 9, which compared to the amount of people allowed by the NY Limousine law, is impossible. Also, there were some pickup … Read more

Meteo sanctum

The project reflects on how people in ancient times defined natural and weather phenomena. The proposal is to create an open public space – Inspired by the concept of an ancient sanctuary with places that used to be built for worship and predictions of weather conditions, the Meteo Sanctum consists of digital indicators that allow … Read more

Stickers in Barcelona, el Gotico

Objective The objective of the project is to create a database of stickers located in the district of Gotico, Barcelona by collecting geolocated photos, analyzing & sorting them by machine learning and further research to then create a framework for evaluating and improving local economy, artists and political movements marketing strategies. Strategy By collecting geolocated … Read more

Dislocating Creativity

“A Data-Driven Approach to Balancing Creative Class Development and Social Equity in Barcelona” The creative industries have been acknowledged as one of the most important sectors for economic growth and development in current cities worldwide. This sector represents a space of culture where all artistic and creative expression that pro-actively enters into dialogue with new … Read more

A Policy for Digital Carbon Footprint, Barcelona

Every single search query, every streamed song or video and every email sent, billions of times over all around the world – it all adds up to an ever-increasing global demand for electricity, and to rising CO2 emissions too. Our increasing reliance on digital tools has an environmental impact that’s becoming increasingly harder to ignore. … Read more