Multimodal Analyte Sensor Network Segmentation
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Solution Overview
Problem
Conventional analyte monitoring systems are unsuitable and expensive for continuous monitoring over a region of a potential analyte source, as low-cost sensors have high detection limits and suffer from signal drift, cross-sensitivities, and require frequent calibration, while optical-based detectors consume too much power and are costly for wireless sensor networks.
Innovation Solution
A sensor network comprising a combination of high-performance optical sensors and low-cost chemiresistive sensors distributed throughout the detection region, with a local gateway to manage data transmission and reduce power consumption by operating in a low-power mode until analyte concentration exceeds a threshold, allowing for efficient detection and data transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If optical-based analyte detectors are used, then detection limit is reduced, but power consumption increases and cost increases
Solution Approach 1:
The system divides the detection region into multiple zones with different detection requirements. High-performance optical sensors are deployed only in regions where low detection limits are critical, while low-cost chemiresistive sensors are used in other areas. This segmentation allows the system to achieve necessary detection precision without deploying expensive, high-power sensors throughout the entire region.
Solution Approach 2:
Different sensor types are assigned to different locations based on local requirements. The system uses a hybrid architecture where optical sensors with lower detection limits are strategically placed in high-priority zones, while chemiresistive sensors handle routine monitoring in lower-priority zones. This local quality approach ensures that high power consumption is concentrated only where the superior detection capability is truly needed.
2Ease of manufacture
If low-cost analyte sensors are used, then cost is reduced, but detection limit increases and measurement precision deteriorates
Solution Approach 1:
The sensor network is segmented into heterogeneous nodes with different sensor capabilities. Low-cost chemiresistive sensors form the bulk of the network for cost-effective coverage, while a smaller number of high-performance optical sensors are strategically distributed to provide enhanced detection where needed. This segmentation allows the system to achieve overall low cost while maintaining adequate detection limits through the distributed hybrid architecture.
3Reliability
If continuous monitoring is implemented across the entire detection region, then detection coverage is improved, but power consumption and resource utilization increase
Solution Approach 1:
The system implements periodic sampling and event-driven monitoring rather than continuous high-rate sampling at all nodes. Sensors can transition between active and low-power states, with the low-power mode activated when analyte concentration is below thresholds. This periodic action maintains detection coverage while significantly reducing average power consumption across the network.
Solution Approach 2:
The monitoring system dynamically adjusts its operation based on detected analyte concentrations. When concentrations exceed predefined thresholds, the system transitions to high-power, high-frequency monitoring mode. When concentrations remain below thresholds, sensors operate in low-power mode with reduced sampling rates. This dynamic behavior ensures adequate detection coverage during critical events while minimizing power consumption during normal 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
The system provides cost-effective and power-efficient continuous analyte monitoring with improved detection limits and reduced signal drift, enabling accurate and swift detection of analyte concentrations while minimizing unnecessary resource utilization.
Implementation Method 1
identifying an electrical signal generated by an electrochemical reaction of the first analyte sensor or the second analyte sensor
Data Source
AI summary
The present invention involves a multimodal sensor network for analyte detection. A first mode may involve low-power detection and a second mode may involve determining an analyte concentration and transmitting data associated with the analyte concentration. Specifically, the first mode may include establishing an analyte sensor network in a detection region, detecting an analyte in the detection region, and generating an electrical signal in response to the detecting the analyte. In response to the electrical signal exceeding a first threshold, the analyte detection system may operate in the second mode. The second mode may include requesting data associated with the one or more environmental conditions, determining an analyte concentration based on one or more environmental conditions transmitting data associated with the analyte concentration.