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Master in City & Technology 01

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.

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Unequal Blooms: Studying socioeconomic realities of Medellín’s “Eternal Spring”

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MaCT-01 2023-2024

Introduction In recent decades, the importance of urban green spaces and their potential impact on various aspects of urban life has gained significant attention from policymakers, urban planners, and researchers worldwide. The creation and maintenance of green spaces within urban environments have been associated with numerous benefits, including environmental sustainability, physical and mental health improvements, … Read more

‘Black Holes and Revelations’

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MaCT-01 2023-2024

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

45 Years of Piracy: Strengthening Global Maritime Security through Non-Military Approaches

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MaCT-01 2023-2024

Our project embarked on a mission to tackle global shipping piracy without resorting to military action. We faced a major challenge: finding and using publicly available information to craft a proposal that countries and international organizations would support. 1. WHY SHIPPING PIRACY? Within the context of Networked Flows, our directive was to pinpoint potential disruptions … Read more

Art on air

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MaCT-01 2023-2024

Introduction Air quality is a problem in many cities around the world, yet it remains largely invisible to the naked eye. This reality struck us deeply when the four of us, having lived in Barcelona, Lagos, Bangkok, and Medellin – our four cities of origin – came together. Amidst our diverse backgrounds and experiences, we … Read more

‘Gotta Catch ’em All’

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MaCT-01 2023-2024

Co-design & Experience Platform for Public Art as part of Data, Art and the City (5-day workshop led by Leyla Saadi) Adapted from Pokemon-Go, we propose the development of a place-based app that pops the City of Toronto’s public art scene, drives interest and support for local public art and artists, and co-designs future public … Read more

What is creativity?

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MaCT-01 2023-2024

Creativity is often seen as the ability to transcend traditional ideas, rules, patterns, and to create meaningful new ideas, forms, methods, interpretations. But, can we confine its vastness to mere definitions? Furthermore, can the creative output of cities be quantified? A notable attempt to do so was made Inkifi. They composed a data based ranking … Read more

The Future of Public Art

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MaCT-01 2023-2024

In the ever-evolving field of urban development, “The Future of Public Art” sets out to be a project that reimagines the role and impact of art in public spaces. At its core, the project seeks to quantify the value of public art through a systematic approach, anchored in three fundamental pillars: democracy, contextuality, and insightfulness. … Read more

New York Taxi Analysis

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MaCT-01 2022-2023

As the Submission about Data Digital Tools & Big Data II, we analyzed the new york taxi data. We were given the data about Taxi Infomation in New York, in 2016.In this data, there is information, from the data, I made new information, Erased some columns, and fix the data. Reading the data the data … Read more

The City of Marvelous Disorder

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MaCT-01 2022-2023

The City of Marvelous Disorder is a study was conducted during the ‘CaaS studio (City as a Service): The future of cities’ services in the AI times’, that aims to built a methodology on mapping the creative sector and high education ecosystem of Barcelona, with a particular focus on social creative industry that works within … Read more

Digital CO2 ZERO

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MaCT-01 2022-2023

The rising problem of Digital Energy consumption Recent estimates put the contribution of the information and communications Technology, the (ICT) sector – which includes the data centers, devices and networks used for  at around 4 % of global Greenhouse gas emissions. A trend that is unlikely to stop, as the amount of data produced and … Read more

Active Ageing in Barcelona

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MaCT-01 2022-2023

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 Perks of Proximity

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MaCT-01 2022-2023

Clustering advanced industries to facilitate technology transfer in the Barcelona metropolitan region Spain has been at the forefront of pioneering research and innovation that have led to significant contributions to the world of technology. Technology Transfer Technology transfer from research to market seems like a straight-forward and linear process, but such is not the case. … Read more

NYC Taxi Time Traveler

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MaCT-01 2022-2023

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

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MaCT-01 2022-2023

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

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MaCT-01 2022-2023

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

NYC Taxi Trip Duration Predictive Modeling

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MaCT-01 2022-2023

The objective of this exercise is to build a machine learning model that will predict taxicab trip durations based on 2016 NYC Yellow Cab trip record data. Data Fields Based on this, this project will develop a machine learning regression algorithm capable of predicting the duration of a trip based on the variables provided by … Read more

Predicting NYC Cab Ride Duration using ML

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MaCT-01 2022-2023

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

NYC taxi trip duration prediction

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MaCT-01 2022-2023

The data used to prediction is the New York City taxi data from January, 2016 to June, 2016 and New York City weather data from the same time duration. The taxi data has features about pickup time detailed to seconds. Considering the traffic condition could be affected by weekday and hour, so I deconstructed the … Read more

2016 NYC Yellow Cab trip

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MaCT-01 2022-2023

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

New York City Taxi Trip Duration

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MaCT-01 2022-2023

INTRODUCTION The competition is based on the 2016 NYC Yellow Cab trip record dataset. The challenge is to build a model that predicts trip duration for New York City taxis using machine learning. The dataset includes pickup time, geo-coordinates, number of passengers, and several other variables. Based on individual trip attributes, a code was written … Read more

1st Traditional IAAC MaCT ML Competition

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MaCT-01 2022-2023

#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