HVAC Airflow Modeling for Indoor Pathogen Spread Control
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Solution Overview
Problem
Current HVACR systems lack effective mechanisms to dynamically control indoor air quality to mitigate pathogen spread, particularly in complex building environments with varying populations and interactions, as the science on minimizing infection rates within occupied spaces is still evolving.
Innovation Solution
The implementation of an IAQ analytics and control system that utilizes video analytics to capture and analyze human behavior, combined with an airflow simulator to model and adjust HVACR system parameters, including temperature, humidity, and air cleaning technologies, based on real-time and dynamic data to optimize indoor air quality and reduce pathogen spread.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If dynamic people modeling and video analytics are implemented to simulate airflow impact on pathogen spread, then indoor air quality and pathogen control improve, but device complexity and system cost increase
Solution Approach 1:
The system divides the indoor space into multiple zones with different risk levels based on video analytics detection of people density and behavior. Each zone can be independently monitored and controlled, allowing targeted pathogen killing technology deployment only in high-risk areas rather than treating the entire space uniformly.
Solution Approach 2:
The patent introduces an airflow simulator as an intermediary component that bridges video analytics data and HVACR control. The simulator processes complex airflow dynamics and translates them into actionable control parameters, simplifying the overall system architecture while maintaining high reliability.
2Object-affected harmful factors
If pathogen killing technology is deployed throughout the indoor space, then pathogen spread is reduced, but energy consumption increases
Solution Approach 1:
The system applies pathogen killing technology selectively in specific zones rather than uniformly throughout the entire space. Video analytics identify high-risk areas where people density and proximity indicate elevated pathogen transmission risk, and pathogen killing devices are activated only in those localized zones.
Solution Approach 2:
The system dynamically adjusts pathogen killing technology operation based on real-time detection of people presence and behavior patterns. Devices are activated during periods of high occupancy or detected illness symptoms and deactivated during low-risk periods, creating a periodic on-demand operation pattern.
3Loss of time
If real-time video analytics and dynamic modeling are used to control HVACR systems, then response time to pathogen threats improves, but device complexity and computational requirements increase
Solution Approach 1:
The system pre-calculates airflow patterns and creates digital twins of indoor spaces beforehand. When video analytics detect potential pathogen threats, the pre-established models enable rapid simulation and response without requiring complex real-time calculations, significantly reducing response time.
Solution Approach 2:
The patent creates simplified digital representations (digital twins) of the physical indoor space and its airflow dynamics. These copied models allow rapid virtual experimentation and prediction of pathogen spread scenarios without requiring complex real-time physics calculations, enabling fast response to detected threats.
Data Source
AI summary
Described herein are heating, ventilation, air conditioning, and refrigeration (HVACR) systems and methods directed to indoor air quality. HVACR systems and methods are based on dynamic people modeling to simulate and/or to monitor airflow impact on pathogen spread in an indoor space. HVACR systems and methods model an indoor space with pathogen killing technology to deploy the pathogen killing technology. HVACR systems and methods are directed to control administration of a pathogen killing technology to an indoor space based on factors that impact airflow including from dynamic analytics, a known input, and/or detection.