Quarantine air-conditioning system for preventing spread of airborne infectious diseases
Solution Overview
Problem
Current quarantine air-conditioning systems are inadequate in accurately predicting and preventing the spread of airborne infectious diseases, as they fail to effectively reflect the risk of infection based on pathogen features and indoor environmental interactions, and have limitations in detecting airborne pathogens in real-time.
Innovation Solution
A quarantine air-conditioning system that includes an air quality detection unit with complex environmental sensors and a pathogen sensor, which calculates and predicts infection risk using equations that account for temperature, humidity, CO2, TVOC, particulate matter, and occupant information, and instructs a quarantine air-conditioner to perform enhanced operations when risk thresholds are met, utilizing a central control unit for real-time monitoring and notification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional air-conditioning systems are used with basic sensors, then device complexity is low, but measurement precision of pathogen detection and infection risk prediction is insufficient
Solution Approach 1:
The system divides pathogen detection into multiple specialized sensors (viral pathogen sensor, bacterial pathogen sensor, fungal pathogen sensor) that detect different types of pathogens independently. Each sensor targets specific pathogens, enabling precise detection while maintaining modular system architecture that manages complexity through functional segmentation.
Solution Approach 2:
The air-conditioning system integrates multiple functions into a single platform: pathogen detection, infection risk prediction, automated air quality adjustment, and notification services. The central control unit coordinates all these functions, allowing the system to perform diverse tasks without requiring separate standalone devices for each function.
2Measurement precision
If spatially averaged virus detection is used, then device complexity is low, but measurement precision of local infection risk is insufficient
Solution Approach 1:
The system divides the indoor space into multiple monitoring zones with dedicated sensors in each zone. This spatial segmentation enables localized pathogen detection and infection risk assessment for each specific area, providing precise local risk prediction rather than averaged whole-space data.
Solution Approach 2:
Each monitoring zone has its own pathogen detection capabilities and infection risk prediction parameters tailored to local conditions (occupant density, ventilation characteristics, activity patterns). This allows the system to provide customized, location-specific risk assessments that reflect local quality differences across the space.
3Reliability
If real-time pathogen detection and response is implemented, then reliability of infection prevention is improved, but loss of time for system response and energy consumption increase
Solution Approach 1:
The system employs periodic pathogen detection at predetermined time intervals rather than continuous monitoring. The central control unit adjusts air quality parameters (temperature, humidity, ventilation rate) periodically based on detected pathogen levels and predicted infection risk, reducing energy consumption while maintaining reliable infection prevention through timed intervention cycles.
Solution Approach 2:
The system continuously monitors pathogen levels and infection risk predictions, then provides feedback to automatically adjust air conditioning operations. When pathogen levels exceed thresholds or infection risk becomes high, the system responds by enhancing air purification and ventilation, creating a closed-loop control that maintains reliability while optimizing energy use based on actual conditions.
4Measurement precision
If comprehensive air quality parameters are monitored, then measurement precision of infection risk is improved, but device complexity and information processing requirements increase
Solution Approach 1:
The system extracts and prioritizes only the most critical air quality parameters (temperature, humidity, CO2 concentration, TVOC, particulate matter) that have the greatest impact on infection risk, rather than monitoring all possible air quality metrics. This selective extraction reduces data processing burden while maintaining sufficient precision for accurate infection risk prediction.
Solution Approach 2:
The system transforms multiple raw air quality parameters into a unified infection risk prediction metric through standardized calculations. By converting diverse parameters (temperature, humidity, pathogen concentration, occupancy) into a single comprehensive risk index, the system simplifies information processing and presentation while preserving the precision benefits of comprehensive monitoring.
Data Source
AI summary
The present disclosure provides a quarantine air-conditioning system for preventing a spread of airborne infectious diseases, and more particularly, to a quarantine air-conditioning system for preventing a spread of airborne infectious diseases, which may accurately predict a risk of infection with airborne infectious diseases to thus effectively prevent a spread of the airborne infectious diseases, and a method for preventing a spread of airborne infectious diseases using the same.