Air Sampler with Integrated Pathogen Detection Modules
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Solution Overview
Problem
Current methods for pathogen detection in metagenomics lack efficient and real-time monitoring capabilities, particularly in environments where rapid identification and mitigation of airborne pathogens are crucial, such as in enclosed spaces.
Innovation Solution
A system comprising an air sampler with integrated detection modules for genetic analysis, anomaly detection, pathogen-specific detection, and pathogen-profile characterization, which collects and processes air samples to detect organic loads and identify pathogens, triggering notifications and suggesting mitigation actions based on threshold exceedance and risk assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If traditional pathogen detection methods are used, then pathogen identification can be performed, but real-time monitoring capability is lacking and detection speed is slow
Solution Approach 1:
The detection system is segmented into multiple specialized modules: organic load detection module for rapid initial assessment, pathogen-specific detection module for targeted identification, and pathogen-profile characterization module for comprehensive analysis. This segmentation allows parallel processing and rapid sequential detection, reducing overall detection time while maintaining accuracy.
Solution Approach 2:
The system performs preliminary organic load detection before conducting full pathogen identification. By first detecting the presence and quantity of organic material, the system can prioritize samples that require full analysis, enabling rapid screening and reducing the time needed for complete pathogen characterization in urgent cases.
2Measurement precision
If comprehensive pathogen detection and characterization is performed, then accurate pathogen identification is achieved, but system complexity increases
Solution Approach 1:
The complex detection process is divided into distinct functional modules, each responsible for a specific aspect: organic load detection, pathogen-specific detection, and pathogen-profile characterization. This modular architecture allows each module to be optimized independently while maintaining overall system precision, and enables selective activation of modules based on detection needs.
Solution Approach 2:
The organic load detection module serves as an intermediary that bridges simple presence/absence detection and comprehensive pathogen characterization. By first assessing organic load, the system can guide subsequent detection steps, ensuring high precision while managing complexity through hierarchical processing.
3Productivity
If continuous monitoring is implemented, then real-time pathogen detection is achieved, but energy consumption increases
Solution Approach 1:
The system implements periodic monitoring with variable intervals based on detected conditions. During periods of low organic load, monitoring frequency is reduced to conserve energy. When organic load exceeds thresholds or anomalies are detected, the system increases monitoring frequency, achieving continuous oversight capability while optimizing energy consumption through adaptive periodic action.
Solution Approach 2:
The system uses feedback from organic load detection results to dynamically adjust monitoring intensity and energy consumption. When organic loads are within normal ranges, the system operates in low-power mode. When thresholds are exceeded or anomalies are detected, feedback triggers increased monitoring activity, ensuring high productivity during critical periods while minimizing energy use during stable conditions.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables near-real-time detection and characterization of airborne pathogens, facilitating rapid risk assessment and mitigation in various environments, improving safety and reducing the spread of pathogens.
Implementation Method 1
an air sampler located in the environment and configured to draw ambient air from the environment through an inlet of the air sampler and onto a sampling medium within the air sampler
Implementation Method 2
a first detection module integrated within the air sampler and configured to detect organic matter present in pathogen samples
Implementation Method 3
a second detection module configured to detect presence of a set of pathogens in the environment via genetic analysis of a pathogen sample
Data Source
AI summary
One variation of a method for detecting pathogens in an environment includes, during a first sampling period: triggering collection of a pathogen sample from ambient air in the environment by an air sampler; and tracking a first organic load of the first pathogen sample via a detection subsystem integrated within the air sampler, the first organic load representative of a first amount of organic matter present in the first pathogen sample. In response to the first organic load exceeding a threshold organic load defined for the environment, the method further includes: interpreting presence of a set of pathogens in the environment via genetic analysis of the first pathogen sample; and, in response to detecting presence of a first pathogen, in the set of pathogens, in the first pathogen sample, transmitting a notification indicating presence of the first pathogen in the environment to a user associated with the environment.