Vehicle Crash Prediction in New York City

Project Aim In this project we aim to predict the type of vehicle crash that can be foreseen in the city of New York based on the traffic volume, using Graph Neural Networks (GNNs). To develop this machine learning model we use 3 different datasets. The model could hold potential if developed further, to be … Read more

To bike or not to bike?

Bike route classification using Graph Machine Learning The goal of the project was to develop a graph machine learning model that would predict existence of bike routes in Singapore based on collected geodata. Because the bike routes were represented by graph edges, that was also our classification type. Data Exploration & Research Topic We choose … Read more

Barcelona Program

Block Classification This project aims to classify urban blocks in Barcelona, focusing on the districts of Saint Martí and Eixample, based on their dominant functions. By identifying the primary uses of these urban blocks, we can gain insights into the spatial organization and functional distribution within the research area. Saint Martí and Eixample, two vibrant … Read more

Rental Price Predictor – Amsterdam

Introduction Accurate prediction of rental prices poses a significant challenge in dynamic real estate markets such as Amsterdam. Our research project explores the use of graph-based machine learning to improve the accuracy of such predictions. This methodology could be of interest to various actors in the real estate sector, including brokers, investors, and urban planners. … Read more

migrAItion

Studying migration is crucial for urban planners and architects to anticipate and accommodate the influx of people into cities, ensuring the development of robust infrastructure that can support this growth. As migration patterns shape demographic changes, understanding these trends allows cities to plan for adequate housing, transportation, healthcare, and educational facilities. This foresight is essential … Read more

Real-time Daylighting Performance for Adaptive Reuse Planning

This project aimed to develop a daylight predictor to facilitate and generate well-informed adaptive reuse projects, with a specific focus on providing sustainable design solutions for low-income housing. Los Angeles (LA) was selected as a case study due to its proactive open data initiatives and commitment to adaptive reuse. This proposal provides a snapshot of … Read more

FacAid + Chatbot

In a world where urban areas are predominantly developed and the heat island effect is intensifying, the construction industry significantly contributes to environmental challenges. Instead of focusing on tools that promote new construction, our goal is to provide a tool that analyzes existing buildings and suggests improvements. This approach aims to enhance sustainability and mitigate … Read more

Materializer

Introduction Our project, Materializer, leverages the power of multiple self-trained machine learning models to predict material quantities based on an image uploaded by the user and the building coordinates. This innovative approach utilizes image segmentation to isolate buildings, image classification to read material pixels, and a height prediction model for buildings lacking height information in … Read more

MY PARKS : Predicting Miami City’s Parks Scores based on Amenities and Businesses

Miami Parks Prediction GraphML Project

Rethinking Urban Spaces Parks and green areas are critical in cities as they provide spaces for people to meet, interact, and find a social life. They contribute significantly to the mental and physical well-being of residents, offering a natural respite from the urban hustle. Project Summary: According to google reviews, the most important factor for … Read more

Project Sentinel: Predicative analysis of street lighting and safety

Greater Manchester, one of the largest and most vibrant urban centers in the UK, is characterized by its substantial student population and a dynamic economic landscape. With approximately 120,670 university students during the 2021/22 academic year and a significant number of these individuals studying at the University of Manchester and Manchester Metropolitan University, the region … Read more

THF // MICRO-CITY

The proposed vision for Tempelhof is articulated as a ‘city within a city’ arranged along the two airstrips of the former airport, extending perpendicularly to emphasise a dual directionality. Buildings are conceived as flexible micro-communities built on organic/biodegradable materials, with the possibility of growing or ‘de-growing’ through time.The design strategy aims to trigger a need … Read more

GENDERED GEOGRAPHY​: A SILOM SAFETY INITIATIVE​

“WHAT IS THE FIRST THING THAT YOU THINK OF WHEN YOU HEAR THE WORDS:​ GENDER & BANGKOK? “ 1. BANGKOK’S SPECTRUM OF GENDER (INTRODUCTION)​ Historically, Thai society has grappled with rigid gender roles, which often saw Thai women facing significant challenges and being relegated to positions within the entertainment and sex industries. However, as Thai society … Read more

Invisible Barriers, Visible Caregivers

Introduction Medellin, known as the ‘City of Eternal Spring,’ is a Colombian city located between mountains around the Aburra River Valley. According to the National Census, it is inhabited predominantly by women, as 53.3% of the population is composed of women, and a large portion of them perform in areas such as education, healthcare and … Read more

Guidebook on Urban Degrowth

The Case of Tourism in Barcelona The “Guidebook on Urban Degrowth” explores applying degrowth principles in urban planning to promote social well-being and ecological equity in cities. This thesis develops guidelines to shift from high-consumption economic models to those that emphasize environmental balance and social equity. Focusing on Barcelona, it addresses the challenges of over-tourism, … Read more

PROJET TOKYO

Frist Research Mebolsim What is Metabolism? Building of Metabolsim Masterplan of Metabolism Comaprison, Masterplan Tokyo by Kenzo Tange vs Comptemporary Tokyo Comaprison1 Theory Comaprison2 City Plan Comparison3 Area plan Comparison4Building Comaprison Conclusion

LeCorbunisms

A conversation in which Jane Jacobs and Rem Koolhaas try to get LeCorbusier to think differently about the city… or the opposite! The Challenge We used Conversable Agents and Retrieval-Augmented Generation (RAG) to simulate a discussion between three influential architects: Jane Jacobs, Rem Koolhaas, and Le Corbusier. These theorists have shaped our understanding of the … Read more

Metro Station Prediction in Stockholm

This post describes the development of a method to predict metro station locations using Graph Neural Networks (GNNs). Our journey began with a challenge familiar to urban planners: how to strategically place new metro stations to optimize transportation networks. In this case the city of Stockholm was used as testbed. The Challenge of Data Imbalance: … Read more

WHAT IS ADVANCED AIR MOBILITY?

A multidimensional and multiscalar exploration of the emerging Vertical Urban Transportation landscape. [A] INTRODUCTION “Advanced Air Mobility (AAM) is a rapidly-emerging, new sector of the aerospace industry which aims to safely and efficiently integrate highly automated aircraft into the NAS. AAM is not a single technology, but rather a collection of new and emerging technologies … Read more

Re:New

UP-CYCLING CDW THROUGH RAMMED EARTH TECHNIQUE The project promotes a circular economy for construction demolition waste (CDW), focusing on concrete and brick materials. It investigates the creation of a material system that integrates data-driven demolition mapping, innovative material reuse, robotic manufacturing and a meticulous approach to designing the life-cycle of the material. It uses the … Read more

100-Year Flood Risk Road Intersection Classification

Flood Risk Classification

Beginnings Our project’s concept is to develop a classification model that identifies street intersections (graph nodes) in Stockholm, Sweden, susceptible to flooding during a 100-year flood event. Based on our initial research, we found that graph machine learning operates at three levels: the graph, its edges, and its nodes. With access to a 100-year flood … Read more