The MaCAD is a unique online programme training a new generation of architects, engineers and designers ready to develop skills into the latest softwares, computational tools, BIM technologies and AI towards innovation for the Architecture, Engineering and Construction (AEC) industry.
For our MaCAD Studio project, we wanted to explore the idea of circularity during the assembling/disassembling stage of the various programmatic functions housed by the building structure. The main materials employed are CLT and Reinforced Steel, of which we picked the first to be the focus of our study since it is the primary material … Read more
Introduction In our studio project, we use a combined bottom up and top down approach to develop a mixed use building; designed to integrate multiple functions, including residential, recreational, and commercial, within a single structure. Our goal is to feature a flexible layout, using modular construction techniques and clear circulation patterns, with well-designed junctions. Programmatic … Read more
Spring Summer Autumn Winter Figure 1.1: New York Seasonal Change New York City experiences distinct seasonal changes that shape its environment and urban character. In spring, the city transitions to milder conditions, with unpredictable weather patterns and renewed greenery. Summer brings intense heat and humidity, influencing activity patterns and urban energy demands. Fall is marked … Read more
Rome has a Mediterranean climate characterized by hot, dry summers and mild, wet winters. Average temperatures range from around 8.5°C in winter to about 31°C in summer. The city experiences moderate rainfall, with the wettest months typically being October and November. Climate Analysis In Rome, the bulb temperature, which reflects the combined effect of air … Read more
Austin has a humid subtropical climate (Köppen climate classification: Cfa), characterized by hot summers and mild winters. The city experiences long, hot summers and short, mild winters, with brief transitions in spring and fall. The climate data used in this analysis was obtained from: – Location: Austin-Mueller Municipal Airport, Texas, USA – Weather Station ID: 722540 … Read more
This analysis focuses on Richmond, Virginia in the United States of America. Weather conditions in Richmond are typical of a mid-latitude location. We’ve explored the environmental conditions that shape building design and urban planning in this mid-latitude location. Our focus is on a vacant lot at 701 East Canal Street, in downtown Richmond. This property … Read more
When it comes to designing sustainable urban spaces, understanding the local climate and environmental factors is crucial. This analysis on environmental conditions for Porto focuses on climate, thermal comfort, solar radiation, wind analysis, and urban heat mitigation. Here are the key takeaways from this comprehensive research. Climate Analysis: Understanding Porto’s Unique Conditions Porto’s climate is … Read more
In the rapidly urbanizing landscape of Singapore, the demand for innovative urban planning solutions is paramount to accommodating the growing population while preserving the city-state’s unique cultural and environmental heritage. This project proposes an exploration of a playful design methodology to devise novel urban block typologies tailored to Singapore’s specific needs and constraints. This research … Read more
Abstract This study examines the pressing problem of violence against women in Mexico City, focusing specifically on strategies to prevent the escalation of violence that can lead to femicides. The persistence of gender-based violence in the city is aggravated by socioeconomic disparities, inadequate urban planning, and a deficiency of safe public spaces. The notable increase … Read more
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
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
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
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
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
Who Why: For the Amenities, we selected the following due to its overall correlation with residential real estate and we anticipate that it will give a good indication of how the properties would be priced. By creating bounding boxes around the amenities, with a radius of 1km, we ensure that as much of the graph … Read more
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
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
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
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
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
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
To predict whether a location in Barcelona is a key tourist site or not using graph data and specific contextual features, including the impact of the PEUAT plan on regulating tourist accommodations. The features explored and the URL selected on the Barcelona open data are score or indicator related to the tourism plan PEUAT, Proportion … Read more
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
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
