Partner: University of Arizona
Location: Tucson, AZ
Scope: AQ data analyzed over a 4-month period, research ongoing since March 2023.
Objectives
- Design a research platform to explore innovate methods of indoor AQ monitoring and management.
- Collect datasets on the relationships between air quality and room occupancy for further research.
Solution
- Deployed an air quality monitoring network, enabling real-time collection of CO2 and other indoor environmental data.
- Developed physics-informed machine learning models to predict room occupancy status based on CO2 level dynamics.
Results
- Collected a unique labeled dataset on indoor air quality and its relationship to room occupancy status.
- Developed model will be further implemented for for demand control ventilation systems and the analysis of indoor air quality in buildings.
- Scientific publication is in the manuscript preparation stage.
