Sensor Package Spatial Path Fingerprinting for Reconfigurable Detection
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Solution Overview
Problem
Conventional sensors are limited in their ability to be reconfigured, updated, or deployed in complex arrays, facing issues such as faulty data, environmental constraints, cross-contamination, limited measurement ranges, high power consumption, and security risks, which hinder their performance and flexibility.
Innovation Solution
A system that includes a non-transitory memory and processors to manage sensors as a service platform, enabling sensor upgrades, data processing, and network configurations, allowing for enhanced capabilities, remote management, and integration with machine learning for improved analyte detection and greenhouse gas emission tracking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional sensors are deployed in predetermined configurations, then sensor deployment is simple, but sensor flexibility and reconfigurability are limited
Solution Approach 1:
The patent implements dynamic sensor configurations where sensor arrays can be reconfigured in real-time based on detection needs. The system transitions from static predetermined configurations to dynamic adaptable configurations, allowing sensors to be activated, deactivated, or repositioned virtually through software control without physical reconfiguration.
Solution Approach 2:
The patent creates a universal sensor platform that can perform multiple detection functions through a single deployed array. By implementing multi-functional capabilities including spatial mapping, temporal tracking, and various detection modes within one sensor system, the invention eliminates the need for multiple specialized sensor deployments.
2Measurement precision
If sensors operate with fixed detection capabilities, then sensor design is simple, but detection precision and measurement ranges are limited
Solution Approach 1:
The patent implements variable detection parameters including adjustable sensitivity levels, detection thresholds, and measurement ranges that can be modified through software. The sensor system can change its operational parameters dynamically to optimize precision for different analyte concentrations and detection scenarios without hardware modifications.
Solution Approach 2:
The patent divides the sensor array into multiple independently controllable sensor groups or clusters that can be activated selectively. This segmentation allows different portions of the array to be optimized for different detection tasks, improving overall precision while managing complexity through modular control.
3Reliability
If conventional sensors cannot be updated after deployment, then initial deployment is straightforward, but sensor performance and accuracy cannot be improved
Solution Approach 1:
The patent incorporates updateable memory and reconfigurable logic circuits during initial sensor deployment, preparing the sensor system for future updates. This preliminary action enables subsequent software updates, calibration adjustments, and capability enhancements without requiring physical sensor replacement, thereby improving reliability over time.
Solution Approach 2:
The patent introduces a communication interface and control system as an intermediary between the sensor array and external update sources. This intermediary layer enables remote updates, calibration adjustments, and performance optimizations while maintaining ease of operation through standardized communication protocols.
4Measurement precision
If sensors lack spatial mapping capabilities, then sensor design is simple, but ability to detect origin and spatial distribution is limited
Solution Approach 1:
The patent adds spatial dimensionality to sensor detection by implementing arrays of sensors that can map the three-dimensional space within a container. The system transitions from point detection to volumetric mapping, enabling precise determination of analyte origins, distributions, and movements through spatial coordinate analysis.
Solution Approach 2:
The patent combines multiple sensor elements into integrated arrays that function collectively for spatial mapping. By merging individual sensor detections with positional information and processing them together through coordinate transformation algorithms, the system achieves comprehensive spatial awareness without excessive complexity.
Data Source
AI summary
Methods and system to learn precise sensing fingerprints based on machine learning integration are disclosed herein. In use, the system receives at least one first parameter associated with at least one sensor and associates the first parameter with a pre-identified first digital signature in a signature database. A machine learning system is trained based on the first parameter and the pre-identified digital signature. The system then receives at least one second parameter from the at least one sensor and determines that the second parameter is independent of a digital signature in the signature database. Using the machine learning system, a second digital signature for the second parameter is identified and saved in the signature database.