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.
Introduction The objective of this Data Science project is to investigate the possible evolution that the value of a chess piece may experience when they’re allowed to move on a board of higher dimensions. The project will analyse the movement of the chess pieces beyond the 2d plane and onto the 3d cube, 4d hypercube … Read more
A Data-driven Approach of redefining the Accessibility of the Dispersed Urbanity of the Aegean Archipelago Accessibility is a multifaceted concept that expresses the case of access between two points in space. In the context of islands, accessibility is of utmost importance due to their inherent characteristics of isolation and small size. The Aegean Archipelago in … Read more
22@, an ongoing project in Poblenou, Barcelona aims to promote sustainable development and enhance the quality of life for its residents. However, one of the current challenges faced by the project is the significant noise and air pollution caused by the transportation of construction and demolition waste (CDW) from construction sites to landfills, which adversely … Read more
TRANSFORMING CITIES INTO URBAN FORESTS This principle, proposed by Cecil Konijnendijk, highlights the significant role played by urban forests and other forms of urban nature in promoting our health, well-being, and resilience to climate change. It acknowledges the need to consider various aspects of urban forests to achieve success. It also emphasizes the importance of … Read more
Urban Green Spaces are critical urban infrastructure – equally important to how our city functions as transport networks, and particularly vital to the wellbeing of our community. Urban greening supports Melbourne’s economy, providing cooling and amenity which supports the pedestrian economy and reduces operating costs for local businesses. Melbourne is encouraging more innovative methods for … Read more
Main question. How built heritage affects real estate market in European cities? Hypothesis Let’s look at this question on the example of Barcelona. Let’s single out the city neighborhoods (barrios) where historical buildings are located, and analyze the ratio of average real estate prices to them, in particular, the sale prices of apartments and houses. … Read more
This project explores the relationship between urban heat and mental health in a city using clustering analysis. Four distinct clusters were identified, revealing patterns related to population percentages with mental health problems, urban heat levels, and proximity to industrial areas. Additionally, the study examines the association between urban heat, housing stress, and access to natural … Read more
The city of Mumbai, known as the financial and entertainment capital of India, has experienced a significant surge in housing prices and rents in recent years. The demand for residential properties in Mumbai has been steadily increasing due to factors such as population growth, urbanization, and the city’s thriving job market. In the midst of … 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
OPTIMIZING THE EXISTING WALKABILITY INDEX Urban design plays a pivotal role in shaping the livability of a city, and walkability is a crucial aspect that directly impacts its residents’ quality of life. The City of Melbourne has developed a Walkability Index. This project aims at optimizing the existing framework by integrating key parameters related to … Read more
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
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
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
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 has been applied to a wide range of domains, including transportation, to improve the accuracy of predictions and optimize systems. In the context of taxi services, predicting the trip duration is an essential task to optimize route planning and estimate arrival times. In this post, we present a machine learning approach using Python … 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
#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
