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.
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
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
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
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 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
The experiment parts from a self organizing model that iterates based in the incident sun hours, to later be evaluated in 2 methods: DCGAN’s and PIX2PIX. Problem Statement: The objective is to utilize urban farming strategically in central Budapest to enhance the affordability of student life. The key questions revolve around the potential yield, geometric … Read more
I PROCESS I PROBLEM STATEMENT The model will consider factors such as building orientation, facade modifications, and roof area expansion and tilt, ensuring optimal solar panel placement and alignment to maximize energy generation. By developing this AI generative model, we aim to overcome the limitations posed by Seattle’s climate, accelerate the adoption of solar energy, … Read more
‘Navigating Future Convenience’ PROBLEM STATEMENT The dataset contains information about previous trips taken by users, where each trip is represented as a node in the graph. The edges between the nodes represent connections between destinations visited by the same user. Additionally, the dataset includes attributes such as location details, amenities, time of day, activity type, … Read more
PROBLEM Maximizing energy efficiency and comfort in buildings with strategically designed and placed sun shades for optimal solar heat reduction is becoming crucial in cities especially in arid zones. This raises an important question how can we use new technologies in achieving such goals. ML MODEL SELECTION in 2017 a very interesting model using Image-to-Image … Read more
Challenge to solve The potential for a building to adapt to various uses is primarily determined during the initial stages of the design process. This feature is rarely considered by architects yet has a significant impact of a building’s sustainability. The intention is to provide an early-stage tool that architects can use to test adaptability … Read more
