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.
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
Project Concept Establishing a Martian food colony around a Mohole, designed based on growth morphology of alfalfa for efficient organization and development using L-systems. These terminologies are further explained below. Moholes Moholes on Mars are massive cylindrical excavations in the regolith, reaching up to 1 km in diameter and 7 km in depth. With temperatures … Read more
Our group project is Ant Hill Colony on Mars, which has both above/below ground elements and underground heart, tunnels and pods. The project concept derived from “learning from ant colony,” therefore, the geometry shapes were more organic and natural. Originally, we recreated this by starting with LiDAR technology to identify the soil characteristics, then applying … Read more
Inhabiting Ice Cavities under the Martian Surface Introduction – The Idea For the first settlers on Mars, we have envisioned a colony of Aqua-Miners with the primary task of harvesting water as a resource from the ice beneath Mars’ surface, storing it and recycling it for sustainable use. Our approach to this problem has been … Read more
Sculpting on Mars Martian Environment – Human Habitat – Water Production “Well-Nest” is a Mars colony primarily dedicated to water mining and accommodation.We advocate for the development of a comprehensive system aimed at extracting, storing, and circulating water throughout the colony. Low Terrain Slope; Min Risk of Excavation Challenge; Expose to Solar radiation – Gaining … Read more
View some of the collected data here: Street Types and Property Information Genius Loci was inspired by the work the of Sarah Williams in her book ‘Data action – Using data for public good’. In today’s data-driven world, the use of data has become increasingly pervasive, shaping various aspects of our lives from policymaking to … Read more
UrbanCanvas is an innovative web application designed to provide comprehensive and detailed data for urban areas, empowering users with precise information about plot boundaries, buildings, 3D structures, roads, land usage, and empty plots within a city. This platform seamlessly integrates advanced mapping technologies, data visualization, and analytics tools to facilitate urban planning, real estate development, … Read more
Digital twins or “digital replica” refer to a highly detailed virtual model of a physical building or infrastructure project, and through real-time monitoring the delivery of continuously updated data about systems and construction processes can be recorded within BIM. In a “House of Digital Twin”, the foundation of the house is Building Information Modeling (BIM), … Read more
Concept The purpose of the app was to help with viewing and researching information on different types of amenities (like parks, playgrounds, etc.) near selected locations, based on the available OSM data. It’s based on Grasshopper script that is sent to Rhino Compute and visualized on the web using three.js. Grasshopper base The script is … Read more
In the dynamic landscape of urbanization, migration towards cities is an undeniable trend. With this migration comes a myriad of challenges, notably the exponential rise in land costs and the often haphazard nature of urban development. As cities expand, there’s a pressing need for thoughtful and strategic construction that not only addresses the demands of … Read more
