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.
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
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
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
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
Insights into the effects of weather data in Argentina, with implications for sustainable land management, deforestation and conservation policies, agriculture, industry and economies. Climate change, in particular the decrease in precipitation, is predicted to have significant effects on the living conditions in Argentina, affecting agricultural production, sea level rise, hydroelectric energy. The dataset composition consists … 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
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
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
NOISENSE emerges as a dynamic tool that facilitates the visualization of otherwise visually imperceptible phenomena within spaces. Through sound simulation and virtual prototyping techniques, NOISENSE aims to go beyond the limitations of human auditory perception, thereby enabling the visualization and replication of sound atmospheres. By conceptualizing sound as a spatial field, the online app allows … Read more
Spanning across an expansive natural sanctuary in Pozzuoli, Italy, the site for our study was equally challenging and interesting. The valley-like topography was crowned by a lake in the middle. The programme of imagining a wildlife museum at this site prompted us to think outside the box, to incur minimum impact on the site while … Read more
Abstract This thesis explores experimental approaches when addressing sea level rise challenges , the impacts of land loss due to sea rise and population growth. It delves into considerations associated with innovative approaches while emphasizing the integration of urban syntax and graph machine learning. Drawing upon case studies and open data, underscoring the importance of … Read more
A Multidimensional Study of the Superilla My research starts from observing human behaviour. Often when we face a change in our lives, especially when it wasn’t planned, we feel resistance and it takes time before we accept and embrace it. As you probably know Barcelona in the last few years lived some changes in its … Read more
Harnessing the power of drone-based photogrammetry and artificial intelligence to create a low-cost urban wildfire diagnostic tool. In recent years, the global community has witnessed a significant upsurge in the frequency and intensity of wildfires. Driven by a combination of climate change, urban expansion, and land-use practices, these fires have not only devastated vast natural … Read more
There are different types of loneliness and different causes for each type. The social media induced loneliness as described by Sherry Turkle in her book Alone Together: Why We Expect More from Technology and Less from Each Other (2012) is different from the loneliness of feeling alone in a crowd in a very large city … Read more
Our project focuses on modeling and predicting habitat fragmentation avoidance mechanisms using graphs. We investigate wildlife corridors in Australia, leveraging graph-based approaches to create coherent passages and connect forest areas. By analyzing satellite images, road data, and other metrics, we construct and evaluate graph models that incorporate forest containment, node characteristics, and connectivity. Our goal … Read more
Meanders on the Lower Mississippi River In the battle between architecture and nature, nature tends to win. Therefore, it is important that we understand how rivers move over time so that we can know the best and the worst places to build. Our project studies the Lower Mississippi River from Cairo, Illinois to New Orleans, … Read more
