Tunable UV Irradiance Control for Adaptive Pathogen Removal
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Solution Overview
Problem
Conventional systems for air and water quality management are often fixed to specific wavelengths and use scenarios, failing to adapt to varying environmental conditions, leading to inefficient power usage and reduced lifespan.
Innovation Solution
An autonomous system with tunable output irradiance and decoupled UV light sources, controlled by sensors and machine learning models, allows for adaptive UV light output based on environmental conditions, reducing power consumption and extending system lifespan by activating/deactivating UV sources as needed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional systems remain on during their lifespan, then pathogen removal function is maintained, but power consumption increases and lifespan is reduced
Solution Approach 1:
The system dynamically adjusts UV light source operation based on real-time environmental conditions. Sensors continuously monitor air quality parameters (particulate matter, VOCs, CO2) and the controller activates or deactivates specific UV sources according to current needs, rather than operating continuously. This dynamic control reduces power consumption while maintaining pathogen removal effectiveness when required.
Solution Approach 2:
The system changes operational parameters (which UV sources are active, at what intensity) based on environmental conditions. Different UV sources targeting different wavelengths are selectively activated depending on the detected air quality metrics, allowing the system to adapt its power consumption and treatment approach to match actual pathogen presence and environmental conditions.
2Measurement precision
If conventional systems are directed to specific wavelengths, then specific pathogen targeting is achieved, but adaptability to varying environmental conditions is reduced
Solution Approach 1:
The system segments the UV light output into multiple distinct wavelength sources (e.g., different UV LEDs targeting different spectral ranges). Each wavelength source can be independently controlled and activated based on the specific environmental conditions detected by sensors. This segmentation allows precise targeting of different pathogens while maintaining the ability to adapt to varying conditions by selecting appropriate wavelength combinations.
Solution Approach 2:
The system achieves multi-functionality by incorporating multiple UV sources with different spectral characteristics in a single platform. This universal design allows the system to handle diverse pathogen types and varying environmental conditions using the same hardware infrastructure, simply by adjusting which sources are activated rather than requiring separate specialized systems.
3Reliability
If UV light sources are continuously activated, then air and water quality management is maintained, but system lifespan is reduced
Solution Approach 1:
The system implements dynamic control where UV light sources are activated only when sensors detect conditions requiring treatment. The controller monitors environmental parameters in real-time and adjusts source operation accordingly, reducing cumulative operating hours and extending component lifespan while maintaining quality management effectiveness when needed.
Solution Approach 2:
The system uses its own sensor data to automatically control UV source operation without continuous human intervention. The sensors monitor environmental conditions and the controller autonomously decides when UV treatment is necessary, allowing the system to self-regulate its operation and extend lifespan by avoiding unnecessary activation.
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
The system effectively manages air and water quality by optimizing UV light output based on real-time environmental data, reducing energy costs and prolonging the lifespan of UV light sources, while maintaining reliable performance.
Implementation Method 1
An autonomous system with tunable output irradiance and decoupled UV light sources
Implementation Method 2
controlled by sensors and machine learning models, allows for adaptive UV light output based on environmental conditions
Data Source
AI summary
A system including groups of illuminators configured to provide adaptive irradiance within the ultraviolet spectrum to remove pathogens, particles, and anthropogenic activity from an air mass of a physical environment based on a detection of a presence of and amount of pathogens, particles, and anthropogenic activity in the air mass.