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.
Vocal Commands for Autodesk Revit Problem Despite decades of technological advancement, the core user experience between man and computer has remained nearly unchanged. This tedious and repetitive process requires designers to spend extreme amounts of time that could be saved through updated methods. This thesis explores a potential future for computer user experience, utilizing AI … Read more
Thermal Insight would be a standalone app that optimizes indoor environments by predicting thermal comfort. With simulations from trained models to help enhance occupant comfort and energy efficiency, evaluating metrics like PMV, PPD, and MRT. This tool would help improve well-being and productivity while achieving efficiency goals. Abstract Methodology Use Case Data Analysis Results and … 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
Our project aims to determine suitable workstation arrangement for office typology in a conservation shophouse in Singapore through maximise daylight on the worksurface to achieve 300 lux (to a maximum of 3000 lux) for good lighting condition. In a conservation shophouse, where the building envelope and facade cannot be altered. There are two daylight sources … Read more
Our Generative AI seminar is dedicated to supporting our work at AIA studio, which focuses on sustainable design. Our task is to collaboratively generate a dataset of at least 800 facade images using generative AI techniques. This dataset will be an essential resource for us, enabling advanced research and development in sustainable architectural design and … Read more
We embarked on a fascinating journey through the latest advancements in Image Synthesis and Language Models within the Architecture, Engineering, and Construction (AEC) industry. The course highlighted the transformative potential of generative AI, enabling architects, engineers, and designers to push the boundaries of traditional design processes, streamline workflows, and tackle complex challenges in groundbreaking ways. … Read more
Skin Sense is a project that aims to help users optimize the thermal comfort of their interior spaces by applying skin shaders. Why implement this? What can skin sense help the user with? Once the designer designs the skin for the building facade it has to be analyzed for indoor comfort. To analyze indoor comfort … Read more
DF Predictor aims to revolutionize daylight prediction in architectural design by implementing the conditional generative adversarial network (cGAN) Pix2Pix to predict daylight factors, motivated by the need to improve efficiency and accuracy in daylight analysis. Daylight factor analysis, an integral part of the early design stages and mandated by building codes, is typically lengthy due … 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
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
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
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
