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.
The LegoLizer Vision The core idea behind LegoLizer is to train a machine learning model that can predict and evaluate the use of specific modules to achieve a certain geometry.In this exercise, we use LEGO modules to train and predict on our features. This project leverages the power of computational design and machine learning to … Read more
Abstract 3D-SOLIDS Component Classification tool utilizes machine learning to optimize the placement of essential 3D components such as walls, doors, windows, floors, and railings in residential floor plans. By analyzing spatial features and architectural attributes, it automates and enhances the design process, ensuring accuracy, consistency, and compliance with building standards. This tool aids architects and … 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
Adaptive reuse is gaining traction as a key strategy for urban regeneration and sustainability. This approach repurposes existing buildings, conserving resources and preserving cultural heritage. However, challenges such as economic viability and technical difficulties often complicate these projects. This is particularly evident in urban centers such as Los Angeles, where the re-purposing of heritage buildings … Read more
Our goal was to predict the relationship between the tourist activity zones and the airbnb rentals. Tourism is vital to Spain’s economic growth, with Barcelona as a key contributor, accounting for over 12% of the country’s GDP. TOURIST ANALYSIS AND DATA Tourist spots and zones can be broadly classified to tourist amenities – transits, bus … Read more
Dataset Our database contains more than 181,000 rows, each with comprehensive information. The primary database includes 17 variables, though not all are necessary for our analysis. The most crucial data points are location (latitude and longitude), type of food establishment, type of inspection, inspection results, and risk level. As the person who uploaded the database … 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
Project H.E.A.T, that is Heat Evaluation Assessment Techniques is an attempt to predict Urban Heat Island (UHI) which is the temperature difference caused due to an urban city being much hotter than the countryside around it, due to the built environment and human activities. As per the project hypotheses predicting UHI using Machine Learning might … 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
is a Graph ML Project, to Predict the Potential of agricultural lands according to Soil meniral statistics, River water statistics and waste land types and proximity. Location: Fermanagh and Omagh, Northern Ireland. After extensive research on open-source data, we discovered that Ireland provides a wealth of information. We studied the historical land uses we found … Read more
An imaginary scenario where we dig into one of this era’s social norms but in the upcoming age of intellegence.
Project Focus For our Graph Machine Learning project, wanted to look at the city of Kyoto and Tourism Behavior around Cherry blossom patterns. Specifically, we set out to find out how cherry blossom patterns might affect the behavior and walking paths of tourists within the city. Data Sets We started by collecting our data sets … Read more
GENERATIVE AI Abstract In today’s evolving architectural landscape, the convergence of technology and design offers unprecedented opportunities to enhance human well-being and promote sustainability. At the forefront of this innovation is ISO-COMFORT, a pioneering project that leverages Generative AI to create isometric models emphasizing thermal comfort and sustainable design. This blog post explores the development … Read more
Hypothesis The goal of this research was to investigate if open spatial data could predict Yelp ratings utilizing graph machine learning (GML) methods. We hypothesize that urban phenomena, events, and objects will indicate customer reviews and popularity, and therefore, could be used predict ratings. In particular, we perform edge classification using the DGL library. For … Read more
