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.
Daylight autonomy is a climate-based metric that measures the percentage of occupied hours during which a given space receives a specific amount of light, typically 300 lux, through natural daylight alone. It is used to evaluate energy efficiency in building designs by evaluating how much artificial lighting can be reduced throughout the year (Lorenz et … Read more
Abstract Architectural drawings and construction documentation are critical in the construction industry, serving as the main means of communication between different disciplines and acts as a blueprint on guiding the construction of the built environment. However, errors in these drawings are quite common and often leads to significant delays, cost overruns, and structural issues. This … Read more
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
Roof albedo, the measure of a roof’s reflectivity, significantly impacts urban heat islands, energy consumption, and overall building efficiency. This study aims to analyze how different roof features and materials affect roof albedo in Copenhagen using machine learning techniques. Extreme heat events are rising globally and projected to increase in frequency and intensity, posing a … 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 project derives from our observation that in Singapore, most of hotels are located along the east and southeast areas near Changi Airport. There are very few hotels on the west side of Singapore. We also take into account on factors that tourists and visitors consider when making a reservation. These factors include public transportation, … Read more
The exercise analyses Yelp reviews on restaurants and tries to investigate on how we can leverage the accuracy and the volume of the review information. The data structure then, is built up directly from the YELP web sites and associate the “review id” to a code that than has been analyzed though a RAG method…. and … 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
Project Aim The idea behind the tool is straightforward, that is to hand-sketch louver lines over a facade image to demonstrate the potential reduction in solar radiation on the facade which is linked to a domino effect on the chain of sustainability, as reduction in radiation on the facade will lead to reduction of energy … 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
Introduction Joo Chiat’s shophouses in Singapore are emblematic of the country’s rich Peranakan heritage, blending architectural elements from Chinese, Malay, and European traditions. Established in the 1920s and 1930s, these colorful and intricately decorated buildings are located in a conservation area that underscores both cultural preservation and modern adaptation. Notable for their historical and aesthetic … Read more
In Switzerland, biking to work is highly encouraged and widely practiced. This is facilitated by the country’s extensive network of bike lanes, bike-friendly infrastructure, and commitment to sustainability However, in terms of safety, Switzerland saw 5,287 cyclist fatalities in 2022, up from 3,793 in 2020. Over the past five years, cycling injuries have increased by … Read more
1. Introduction 2. Methodology 2a. Dataset Generation To train our machine learning model effectively, we needed a substantial dataset of at least 1.000 data points. However, conducting CFD simulations is notoriously time-consuming, presenting a significant challenge in generating such a large volume of data efficiently. To streamline the dataset generation process, we broke down the … 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
Predicting median income through Traffic Volume, Green and Paved Surface Analysis For our research, we selected Phoenix, Arizona due to its significant disparity in the distribution of green spaces. As depicted in the image, areas with higher income levels display dense green coverage, whereas lower income areas are predominantly paved. The image above depicts the … 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
The 30-Year Plan for Greater Adelaide(South Australia), initiated in 2010, aimed to shift away from urban sprawl by fostering a more condensed, pedestrian-friendly urban landscape. The plan emphasised revitalising current neighbourhoods, focusing development along transit routes, and introducing mixed-use areas to connect jobs, services, and public transit with residential zones. Recognising the unsustainable nature of … Read more
A Self-Reflection on AI’s Replication and Innovation in Architecture Our group explores the topic of AI-chitect, a self reflection on AI’s replication and innovation in architecture. The proposal is to initialise Vitruvius’ De Architectura using RAG (Retrieval-Augmented Generation) and set the volume of text as a knowledge base from which our journey as the AI-chitect … 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
Why? Coastal erosion is a dynamic and complex process influenced by both natural factors and human activities. Natural causes such as wave action, tidal patterns, weather events, and rising sea levels due to global warming significantly contribute to the gradual wearing away of coastlines. Additionally, human interventions like coastal construction, sand mining, and deforestation exacerbate … Read more
