Reconfiguring a second type of sensor based on sensing data of a first type of sensor

Patent metadata

Field	Value
Publication number	US-12449387-B2
Application number	US-202418440806-A
Country	US
Kind code	B2
Filing date	Feb 13, 2024
Priority date	Feb 15, 2023
Publication date	Oct 21, 2025
Grant date	Oct 21, 2025

Abstract

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.

First claim

What is claimed is:

1. A system, comprising:
a sensor as a service platform that:
receives first sensor data from a first sensor device having a first set of capabilities, wherein the first sensor device responds to at least one chemical, biological, or electromagnetic interaction with the first sensor device;
analyzes the first sensor data to determine a second set of capabilities, wherein the at least a portion of the second set of capabilities is different from the first set of capabilities; and
transmits a sensor update to the first sensor device, wherein:
the sensor update comprises at least one data packet sent from the sensor as a service platform to the first sensor device, wherein the first sensor device is formed from a three-dimensional (3D) monolithic carbonaceous growth, and
the first sensor device activates the sensor update in order to at least one of: increase a sampling rate, improve a data resolution, expand a detection range, provide additional sensing modalities, or modify data processing algorithms.

2. The system of claim 1 , wherein the second set of capabilities corresponds to at least one of, a greater degree of sensitivity of the first sensor device as compared to the first set of capabilities, or a second set of capabilities pertaining to a second sensor, or wherein the second set of capabilities corresponds to an analyte fingerprint that is different than an analyte fingerprint of the first set of capabilities.

3. The system of claim 1 , wherein the sensor as a service platform further receives array sensor data from an array of sensors.

4. The system of claim 3 , wherein the array sensor data is received collectively at the sensors as a service platform by at least one sensor of the sensor array.

5. The system of claim 3 , wherein the sensor as a service platform further manages the array of sensors, wherein the manage includes increasing or decreasing sensor capabilities for each sensor of the array of sensors.

6. The system of claim 1 , wherein the first sensor data is received at the sensors as a service platform from the first sensor device.

7. The system of claim 1 , wherein the first sensor data is received at the sensors as a service platform from a central sensor node associated with the first sensor device.

8. The system of claim 1 , wherein the first sensor data is received at the sensors as a service platform from another sensor device associated with the first sensor device.

9. The system of claim 8 , wherein the another sensor device and the first sensor device are configured in a mesh network configuration.

10. The system of claim 1 , wherein the first sensor device is an edge device.

11. The system of claim 10 , wherein the first sensor data is processed by the first sensor device prior to being received by the sensors as a service platform.

12. The system of claim 1 , wherein the sensor update affects the first sensor device as well as at least one other sensor device.

13. The system of claim 12 , wherein the at least one other sensor device is in a same sensor asset class as the first sensor device.

14. The system of claim 1 , wherein a resonant frequency of the 3D monolithic carbonaceous growth is based at least in part on either or both of a permittivity and a permeability of a material associated with the first sensor device.

15. The system of claim 1 , wherein the first sensor device is a split-ring resonator (SRR) on or embedded in a material, wherein the SRR includes a resonance portion, wherein the resonance portion is configured to resonate at a first frequency in response to an electromagnetic ping when a state of the material exceeds a threshold, and is configured to resonate at a second frequency in response to the electromagnetic ping when the state of the material is beneath the threshold.

16. The system of claim 1 , wherein the first sensor device is integrated within a label configured to be removably printed onto a surface of a package or container, and the label comprises one or more carbon-based inks.

17. The system of claim 1 , wherein the first sensor device is carbon-based and is functionalized with a material configured to react with each analyte of a first group of analytes.

18. The system of claim 1 , wherein the first sensor device includes a three-dimensional (3D) graphene layer, wherein the 3D graphene layer is biofunctionalized with a molecular recognition element configured to alter one or more electrical properties of the 3D graphene layer in response to exposure of the molecular recognition element to an analyte.

19. The system of claim 18 , wherein the molecular recognition element is a biological material configured to selectively bind with the analyte.

20. The system of claim 1 , wherein the first sensor device is a three-dimensional (3D) carbon-based structure configured to guide a migration of electrically charged electrophoretic ink particles dispersed throughout the 3D carbon-based structure, the electrically charged electrophoretic ink particles responsive to application of a voltage to the 3D carbon-based structure.

21. The system of claim 1 , wherein the sensor as a service platform further receives second sensor data from the first sensor device, wherein the second sensor data corresponds to the second set of capabilities.

22. The system of claim 1 , wherein the second set of capabilities comprise at least two of:
increased sampling rate;
improved resolution;
expanded detection range;
additional sensing modalities; or
enhanced data processing algorithms.

23. The system of claim 1 , wherein the determination of the sensor update is based on at least one of:
historical sensor data;
environmental conditions;
user preferences;
application requirements; or
available system resources.

24. The system of claim 1 , wherein the first set of capabilities include a first grouping of analytes, and the second set of capabilities includes a second grouping of analytes, wherein the second grouping includes the first grouping as well as additional analytes.

25. The system of claim 1 , wherein the first set of capabilities include a first set of preconfigured frequencies for a split ring resonator, and the second set of capabilities include a second set of preconfigured frequencies for the split ring resonator, wherein the second set of preconfigured frequencies includes the first set of preconfigured frequencies as well as additional frequencies.

26. The system of claim 1 , wherein the second set of capabilities corresponds to an analyte fingerprint that is different than an analyte fingerprint of the first set of capabilities.

27. The system of claim 1 , wherein the sensor update with the second set of capabilities is transmitted to the first sensor device as a wireless communication transmission.

28. The system of claim 27 , wherein the wireless communication transmission comprises:
a series of electromagnetic pulses encoding instructions for implementing the second set of capabilities; and
wherein the first sensor device is configured to:
receive the wireless communication transmission,
decode the instructions from the electromagnetic pulses, and
implement the second set of capabilities based on the decoded instructions.

29. The system of claim 1 , wherein the system further causes:
generating wireless communication packets encoding the s

Assignees

• Lyten Inc

Inventors

• Cook Daniel
• Stowell Michael
• Vanheusden Karel
• Gibbs George Clayton
• Nicole Jacques
• Montalvo Carlos
• Matthys Kyle
• Lanning Bruce
• Lim Sung
• Chmiola John

Classifications

• G01N2027/222

  for analysing gases · CPC title

• G01N27/447

  using electrophoresis · CPC title

• G01N27/4145

  specially adapted for biomolecules, e.g. gate electrode with immobilised receptors · CPC title

• G01N27/221

  by investigating the dielectric properties (using microwaves G01N22/00; measuring loss factors or dielectric constants per se G01R27/26) · CPC title

• G06Q50/06

  Energy or water supply · CPC title