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.
London is a city with high density of bike lane networks, and the high costs on metro drives people using bike more. But how people interact with different factors such as tree canopy, amenities and the urban form? Data preparation To start the analysis, I download the bike lane network sample area from Openstreetmap. Urban … Read more
A Study on the Back of the Road, Factors Forming Streets, and Crime Relationships in the 23 Wards of Tokyo, Japan. 2023, Tokyo is the one of megalopolis. Tokyo has built a megalopolis unlike any other in the world. The megalopolis of Tokyo is depicted in Japan’s representative culture, anime, and manga, and the city … Read more
Starting in 2015 urban development spread beyond the administratively defined Melbourne metropolitan area, into Greater Geelong and the Shire of Mitchell. The Melbourne Metropolitan Region or Greater Melbourne comprises 31 Local Authority Governments (LGA, municipalities and shires) aggregated in 6 metropolitan partnerships. Two of them, Inner and Inner South-East allocate the metropolitan core. This project … Read more
The New Delhi Material Repository and Urban Mining project focuses on the city’s sustainable development by implementing the principles of urban mining and establishing a material repository. As the capital city of India, New Delhi holds significant historical and governmental importance, with its urban fabric comprising a combination of planned and unplanned elements. However, with … Read more
Considering the imminent demolition and in-situ rehabilitation of highly dense slum settlements, how might the application of generative algorithms facilitate the maximization and optimization of housing units within the existing spatial constraints? The slums and the unauthorized colonies are located across Delhi to identify which zones needs in-situ slum rehabilitation, there are over 700 slum … Read more
Recycling construction materials is of paramount importance in a city like Barcelona due to its numerous environmental, economic, and social benefits. Barcelona, like many urban centers, faces challenges related to rapid urbanization, resource scarcity, and environmental sustainability. By implementing a robust construction material recycling concept, the city can significantly reduce its construction waste, lower its … Read more
The Boulevard Method utilizes big data analytics and multi-objective optimization processes to map the existing materials building stock and propose adata-driven urban strategy for the future densification of the city of Helsinki. By making the hypothesis that certain roadways will become obsolete in the future due to the transformation of urban mobility, this study analyzed … 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
