IMMERSIVE ENVIRONMENT
AND VISUALIZATION
Interactive exploration through immersive visualization environments is a backbone of TRACE lab’s research. Such immersive environments provide a perfect space in which to design and develop novel data visualization approaches and tools towards making heterogenous data accessible and insightful. Visualization environments enhance the research projects currently underway at TRACE lab by supporting the study of new approaches to understanding, designing, and studying the built environment.
Given the advances in digital technology over the pandemic, much exciting change and upgrades are now available in this sphere. Some initial investigations of immersive environments were part of an exhibit of Data Homebase at the Federation of Canadian Municipalities (FCM) Annual Conference and Trade Show in Toronto, May 2023 in collaboration with Avi Friedman. The exhibit showcased the ‘Data Homebase’ as a rethinking of how we build our homes in response to the challenges of climate change and social equity. The research consolidates and analyzes disparate data sources about our homes to inform how we balance decisions involving affordability, construction waste, energy use, and carbon emissions. Through the immersive visualization the goal to transform housing data through visualization into actionable knowledge was clearly in display. The research investigates the feasibility of tackling housing supply via a circular economy, where materials and buildings are kept in use for as long as possible to reduce waste and promote future use architecture and design preservation. This project and exhibit at FCM were supported by the Canada Housing and Mortgage Corporation (CMHC) and the Peter Guo-Hua Fu School of Architecture.
Team
Naomi Keena, Principal Investigator
Daniel Rondinel
Martha Milagros Pomasonco Alvis
Alexandre Bouffard
Seva Team
Naomi Keena (School of Architecture, McGill, Director TRACE lab)
Anna Dyson (Yale University, Director Yale CEA)
Mohamed Aly Etman (Yale University, Yale CEA)
Learn more here: https://www.cea.yale.edu/research-frameworks/seva