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.
Viladecans greeted us with an unexpected tranquility. We arrived to the city on the commuter train from Barcelona, opposing the flow of morning commuters. The station was empty. A single street, lined with abandoned plots and industrial sheds led us up the hill into the town. A few hundred metres later the scene couldn’t be … Read more
1. Abstract While studying about phenomenology and livability, it’s expression and its governing aspects, it is essential to recognise the true meaning of it. Phenomenology is reffered to the lived experience of objects, space and other surroundings. It is also important to understand the how, when and where of the experiences and what experiences are … Read more
Creating a streamlined pipeline to visualize and extrapolate financial data enabling a correlation with spatial geo-specific information. The World and all countries alike have been increasingly more susceptible to events and developments in the geo-political theatre. It is not surprising that the world’s top two economic and military superpowers play a pivotal role in this … Read more
By 2100, the global temperature is forecasted to increase from 2 to 4 degrees Celsius due the effects of Greenhouse Gases Emissions and Human Activities. The City of Viladecans has developed a Vision by 2030 which expects the city to become EMISSIONS NEUTRAL, and EMISSIONS NEGATIVE by 2050. For approaching this goal, HYPENERGETIC VILADECANS establishes … Read more
Barcelona is a city that in the last decades has become one of the focal points of global mass tourism. Tourists have become part of daily life in the city. The aim of this study was to investigate how tourists and locals experience the city differently, focusing specifically on the topic of noise. The study … Read more
In the dynamic landscape of global innovation, understanding the intricacies of what drives or hinders progress is crucial. This post dives deeper into the innovation data concerning EU countries, aiming to decipher it visually for clearer insights. Leveraging the Global Innovation Index 2022, which assigns each nation an innovation score, this project set out to … Read more
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
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
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 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
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
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
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
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
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
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
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
#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
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
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
