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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Punta Vagno

Punta Vagno! was developed by Kriti Bhavesh Nirmal, Maddalena Caviglia, Noé Guérin, Sophie Köcher-Schulz, Maria Augusta Kroetz, Étienne Lajoie-Asselin, Joshua Mingers, Marta Pianta, with the support of trainers from the Vienna University of Economics and Business, the Institute for Advanced Architecture of Catalonia, the University of Genoa and ALDA, during the Green Skills for Cities … Read more

‘Optimizing Barcelona’

Before the implementation of Cerda’s radical expansion plan, Barcelona was bound by their medieval walls and making every effort to accommodate its overflowing population. Cerda’s plan took into account scientific objectives that would create a city that is not just a well planned co-habiting space but also user-centric. Some of his objectives were gardens in … Read more

GREENOVA

GREENOVA was developed by Dominik Sawallisch, Karim Abillama, Andrea Gnaccarini, Manuel Harm, Maria Magkavali, Moritz Knappinger, Moritz Dahlmanns, Davide Casalino, with the support of trainers from the Vienna University of Economics and Business, the Institute for Advanced Architecture of Catalonia, the University of Genoa and ALDA, during the Green Skills for Cities project, co-funded by … Read more

GREENWAVE

GREENWAVE!

SUSTAINABLE DESIGN FOR CIRCULAR CO-PRODUCTION OF ECOLOGICAL SERVICES. GREENWAVE was developed by Ben Bello, Can Xu, Erum Khaled, Manuel Beca, Lucia Mack, Parshav Sheth, Zerihun Tassano, with the support of trainers from the Vienna University of Economics and Business, the Institute for Advanced Architecture of Catalonia, the University of Genoa and ALDA, during the Green … Read more

From Diversity to Sustainability

Tackling Food Waste in Barcelona’s Multicultural Culinary Scene Introduction Within the framework of the circularity in the built environment, where Material Flow Analysis (MFA) and system maps have played a crucial role, Barcelona’s multicultural culinary scene emerges as a fascinating case study. In this dynamic city, the convergence of diverse culinary traditions is not only a … Read more

[RE]CONSTRUCT

This research project aims to investigate the lifecycle of commonly used construction materials in Barcelona, analyse the materials being demolished in the city, and explore the waste management practices employed by Barcelona for construction and demolition waste. The primary objective is to provide valuable insights into the environmental impact and sustainability of construction materials, identify … Read more

New York Taxi Analysis

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

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

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

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

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

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

NYC Taxi Trip Duration Predictive Modeling

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

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

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

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

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

#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