IAAC’s Master in City & Technology (1 or 2-year program) is a unique program oriented towards redefining the analysis, planning, and design of twenty-first-century cities and beyond. The program offers expertise in the design of digitally enhanced, ecological and human-centered urban environments by intersecting the disciplines of urbanism and data science. Taking place in Barcelona, the capital of urbanism, the Master in City & Technology is training the professionals that city administrations, governments, industries, and communities need, to transform the urban environment in the era of big data.


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Decoding Critical Urban Theory

Harnessing AI to deconstruct text to visuals Introduction Welcome to our exploration of urban theory, where we decipher the complexity of urban theory through the lens of imagery and aphorisms. We—three students with diverse perspectives—have delved into the intricate narratives and critical readings to let us translate them to critical urban thinking. This blog post … Read more

Slo-Mo-Go: Tourism in Slow Motion

A digital tool proposed to re-boost the economy of Ciutat Vella, Barcelona Overview Ciutat Vella being the oldest district of the city of Barcelona was founded in the 1500 BC. The Ciutat Vella district was a very important economic hub for Barcelona. But in the recent times, the district faces problems that are characterised by … Read more

Promised Land

Mesh representation of MIDI

Mapping America’s Genrescape Promised Land, Chuck Berry’s early representation of modern rock and roll, blurs racialized difference in genre origin, fueling the hybridization of genre categorizes, resulting in America’s current rich music tapestry. MIDI data correlated to synaesthetic representations of color is crystalized and in a dense three-dimensional mesh and place qualities are correlated to … Read more

Routing Accessibility

Background Public transportation plays a crucial role in urban planning globally. Extensive research indicates that bus transit has become a highly favored mass mobility system. This preference stems from its cost-effective infrastructure, flexible planning, and discrete architecture that supports incremental growth. Bus transit systems exhibit lower infrastructure costs compared to rail or subway networks, making … Read more

Environmental Asset Resilience

The Environmental Asset Resilience (EAR) Tool is a response to the pressing global challenge of environmental instability, particularly in urban areas. These areas face substantial costs associated with environmental problems and climate change. However, decision-making in addressing these issues is complicated by conflicting priorities, limited resources, and a lack of expertise. The EAR Project aims … Read more

FOLLOWing FOOT.AI

Unraveling Footfall Patterns for Enhanced Urban Planning: A Spatial and Temporal Analysis Introduction Footfall prediction plays a crucial role in urban planning decision-making processes. Understanding the intricate relationship between footfall and its two dimensions—space and time—is essential. In this project, we delve into the workflow and key findings of a project aimed at comprehending the … Read more

GenCity – An intervention enabler for Co-creating Urban Designs

Alejandro Aravena, renowned for his role in facilitating the recovery of a city struck by an earthquake and a tsunami, asserts that Participatory design transcends mere inclusivity and offers enhanced efficiency. Despite recognizing the significance of public participation in urban planning, we delve into the persisting factors that hinder its optimal efficiency. Conventional methods may … Read more

Identifying formal housing projects, New Delhi

During the Internet of Building studio we developed a strategy of predicting the typologies of buildings in New Delhi, India by data, using algorithmic approaches as KMEANS, DBSCAN and PCA aswell a a heuristig rule-set. The objective of this project is to predict if a building in New Delhi is part of a formal settlement … Read more

Predicting the future densification Helsinki along its former transportation infrastructure.

OVER THE NEXT FEW DACADES HELSINKI EXPECTS TO ADD AROUND 250.000 NEW RESIDENTS IN 30-40KM OF TRANSFORMED MOTORWAY – LIKE HIGHWAYS PROJECT DESCRIPTION: In the future, a transition from highways and roadways to boulevards is anticipated due to a projected decrease in the number of cars. This shift is expected to address several issues commonly … 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

Gridscape.ai

INTRODUCTION Urban planning decisions have a significant impact on the development of cities, and using machine learning can provide decision-makers with valuable insights to make informed decisions. By clustering urban areas based on various factors such as population density, built density, POI density, green cover, and build diversity, we can reveal spatial patterns that can … 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