Goals
The built environment plays a fundamental role in hour daily life. It impacts our health, performance, stress levels, social relations, and even the contagion of COVID-19. This project explores expanding the Building Performance Analytics towards a dynamic spatiotemporal framework, studying the characteristics of spaces combined with human activities and organizational processes that influence everyone’s lives.
This semester’s specific goal is to explore the spatiotemporal dynamic of COVID-19 pandemic and its spread in built environments. The dynamic of the spread has been modeled from a virus-centric perspective, at cities and global scales. The current models do not incorporate spatial variables beyond social distance. Even though research indicates that one of the main routes of virus transmission are droplets in built environments, including airflows.
We will work on 3D modeling, spatial analytics, agent-based simulations, process simulations, CFD and airflow simulations, and mathematical models of the virus spread.
Issues Involved or Addressed
On the one hand, current spatial analytics focuses on the static aspects of a building. On the other hand, dynamic variables such as a pandemic spread, focus on the mathematical models. Spatiotemporal modeling and simulation will merge the dynamic variables inside spaces, focusing on analyzing human-centered outcomes, such as performance, health, stress levels, and social interactions.
Methods and Technologies
Academic Majors of Interest
- Business›IT Management
- Computing›Computational Science and Engineering
- Computing›Computer Science
- Computing›OMSCS synchronous
- Design›Architecture
- Design›Geographic Information Science and Technology
- Engineering›Aerospace Engineering
- Engineering›Health Systems
- Engineering›Industrial Engineering
- Other
- Sciences›Psychology
- Sciences›Statistics
Preferred Interests and Preparation
Areas: Computational Design, Architecture, Computer Science, Industrial Engineering, Systems Engineering, Business Analytics, Psychology, Statistics.
Background/interest: Experience or willingness to learn modeling and simulation.
Meeting Schedule & Location
Team Advisors
- Georgia Tech Research Institute
- Georgia Tech Research Institute