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.
In an era where Artificial Intelligence (AI) is rapidly evolving, understanding its potential and risks is crucial. To explore these dimensions, we staged a fictitious debate featuring three contrasting AI agents. This debate delves into the ethical implications, societal benefits, and possible downsides of an advancing AI era. Project Overview This project staged a fictitious … 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
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
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
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
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
Abstract The project explores the implementation of machine learning models to generate LEGO building instructions manuals and providing a detailed description of the set. We employee diffusion models along with LLM (Large Language Model) to generate both the images of the Lego set and its description. LoRA (Low-Rank Adaptation) we train a stable diffusion model … 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
https://github.com/ronmaccms/llm-chatbot.git Can AI Help Us Regulate Itself? AI is rapidly transforming the world. One critical question is whether AI can help regulate itself. By training a LLM on a comprehensive set of research papers, we can explore AI’s potential to provide insights into its own governance and ethical use. The research investigates how national policies … Read more
Artificial Inspiration – Dissecting the Creative Process Creativity is often viewed as a uniquely human trait, emerging from the processes of study, interpretation, replication, and mixing variables to create new combinations and results. This project explores whether it is possible to develop a framework based on these principles that AI can reproduce and whether this … 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
In our increasingly interconnected world, the relationship between humans and AI has often been characterized by a master-slave dynamic. This imbalance raises significant ethical and social implications, necessitating a shift towards mutual respect and collaboration. Our vision reimagines societal structures as rhizomatic connections: non-hierarchical, interconnected, and decentralized. We envision a coalition of all intelligences—biological, artificial, … Read more
Introduction In 1950, Alan Turing posed a fundamental question, “Can machines think?”. Our exploration aims to extend this quest by considering additional questions: can machines develop the higher-order thinking described, as described in Bloom’s taxonomy? Can they create, dream, or imagine? To understand imagination and machine creation, we first examine perception, i.e., the processes of … 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
Setting the Scene In today’s digital landscape, our interactions are increasingly mediated by technology itself rather than as a medium for human communication. This shift creates an illusion of connectivity while fostering isolation, often trapping us in algorithm-driven echo chambers that reinforce our beliefs. Artificial intelligence now guides our lives, listening, learning, and providing information … Read more
AI in the Anthropocene The architectural profession is currently at a critical juncture, faced with the dual challenges of advancing artificial intelligence (AI) and the escalating climate crisis. Many architects harbour fears of obsolescence as AI’s capabilities expand, potentially automating tasks that traditionally require human expertise. This concern is not unfounded, as AI-driven tools increasingly … 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
