Breath VOC Sensor Array for Real-Time Drowsiness Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods fail to effectively detect conditions such as drowsiness and fatigue in individuals, leading to a significant risk of accidents and associated damages, as they are invasive, costly, and not capable of real-time monitoring.
Innovation Solution
A system utilizing solid-state sensors to capture and analyze volatile organic compound (VOC) biomarkers in an individual's breath, which includes a sensor array and cloud computing for data analysis, enabling non-invasive, real-time detection of drowsiness and fatigue.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional methods are used to detect drowsiness and fatigue conditions, then detection can be performed, but the methods are invasive, costly, and not capable of real-time monitoring
Solution Approach 1:
The patent replaces conventional mechanical or chemical detection methods with an optical sensing system. Solid-state sensors detect volatile organic compounds (VOCs) in breath through optical or electronic means, eliminating the need for invasive procedures while maintaining detection accuracy. The system uses sensor arrays that convert chemical information into electrical signals for real-time analysis.
Solution Approach 2:
The patent introduces breath analysis as an intermediary method between direct physiological monitoring and external observation. By analyzing VOCs in breath that correlate with drowsiness and fatigue states, the system provides indirect but accurate measurement of physiological conditions without direct intrusion into the subject's body.
2Reliability
If conventional methods are used to detect drowsiness and fatigue conditions, then detection can be performed, but the methods are not capable of real-time monitoring
Solution Approach 1:
The patent divides the detection system into modular components: multiple solid-state sensors arranged in arrays, each detecting specific VOCs; a processing unit that analyzes sensor signals; and a control system that generates alerts. This segmentation allows real-time monitoring while managing complexity through functional decomposition.
Solution Approach 2:
The system monitors changes in VOC concentrations in breath over time, detecting parameter changes that indicate drowsiness or fatigue states. By continuously measuring and comparing VOC levels against baseline values, the system achieves real-time detection without requiring complex intervention mechanisms.
3Reliability
If conventional methods are used to detect drowsiness and fatigue conditions, then detection can be performed, but the methods are costly
Solution Approach 1:
The patent employs solid-state sensors that are relatively inexpensive to manufacture compared to conventional diagnostic equipment. These sensors can be produced using standard semiconductor fabrication techniques, making the overall system cost-effective while maintaining reliable detection capabilities through array configurations that provide redundancy and accuracy.
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 provides accurate, non-invasive, and cost-effective detection of drowsiness and fatigue, potentially reducing accidents and healthcare costs by enabling early diagnosis and intervention.
Implementation Method 1
solid-state sensors to capture and analyze volatile organic compound (VOC) biomarkers in an individual's breath
Data Source
AI summary
Systems and methods for diagnosing a condition in an individual by analyzing the individual's breath are provided. Sensors may be configured to capture data associated with the breath of an individual. The data captured by the sensors may include a change in resistance measurements recorded by solid-state sensors when the sensors are exposed to the individual's breath at several different temperatures. This captured data may be analyzed to identify one or more volatile organic compound (VOC) biomarkers in the individual's breath. Based on the identified VOC biomarkers, a condition associated with the individual may be determined. For example, a medical condition, or a condition of drowsiness or fatigue associated with the individual may be determined based on the VOC biomarkers in the individual's breath. In some examples, the sensors may be positioned inside a vehicle for determination of condition associated with a driver of the vehicle.