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.
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
Introduction Milan, Northern Italy’s epicenter, confronts economic and environmental challenges rooted in a shift from agriculture to manufacturing. To secure its future, Milan invests in knowledge, tourism, and place-based innovation, relying on revenue from high-income foreigners, students, and the European Union. Strategic efforts to transition to a green economy focus on renewable energy, waste reduction, … Read more
Introduction Known for its fashion, history, and culture, Milan also faces a pressing environmental issue: it stands as one of the most polluted cities in the World. The challenge of mitigating air pollution in Milan is complex, as it is shaped by a mix of geographical, meteorological, socio-economic, and cultural factors. From the city’s dense … Read more
Community is mostly depicted as a unifying tool that brings a sense of belonging, but does it also act as the root of urban conflict by defining who is an outsider? Through the use of AI, the text Cites or Urbanization? by David Harvey was reimagined as a part of a political discourse and represented … Read more
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
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
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
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
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
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
