公开(公告)号：US20240280526A1

公开(公告)日：2024-08-22

申请号：US18440741

申请日：2024-02-13

Applicant: Lyten, Inc.

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

IPC: G01N27/22 ,  G01N27/414 ,  G01N27/447

CPC classification number: G01N27/221 ,  G01N27/4145 ,  G01N27/447 ,  G01N2027/222

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.

公开(公告)号：US12174090B2

公开(公告)日：2024-12-24

申请号：US18596390

申请日：2024-03-05

Applicant: Lyten, Inc.

Inventor： Michael Stowell ,  Jacques Nicole ,  Carlos Montalvo ,  Daniel Cook

IPC: G01M17/02

Abstract: Resonant sensors for environmental health risk detection are disclosed. A mechanical member may include at least one meso-scale or micro-scale resonator disposed on a surface of the mechanical member. Additionally, the at least one meso-scale or micro-scale resonator may include a plurality of first carbon particles configured to uniquely resonate in response to an electromagnetic ping based at least in part on a concentration level of the first carbon particles within the at least one meso-scale or micro-scale resonator. Further, the at least one meso-scale or micro-scale resonator may be configured to resonate at a first frequency in response to the electromagnetic ping when the mechanical member is in a first state, and may be configured to resonate at a second frequency in response to the electromagnetic ping when the mechanical member is in a second state.

公开(公告)号：US20240272103A1

公开(公告)日：2024-08-15

申请号：US18440806

申请日：2024-02-13

Applicant: Lyten, Inc.

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

IPC: G01N27/02 ,  G01N27/72

CPC classification number: G01N27/02 ,  G01N27/72

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.

公开(公告)号：US20240003779A1

公开(公告)日：2024-01-04

申请号：US18369418

申请日：2023-09-18

Applicant: Lyten, Inc.

Inventor： Michael Stowell ,  Jacques Nicole ,  Carlos Montalvo ,  Daniel Cook

IPC: G01M17/02

CPC classification number: G01M17/02

Abstract: Resonant sensors for environmental health risk detection are disclosed. An adhesive may include at least one meso-scale or micro-scale resonator embedded within a material that comprises at least a portion of the adhesive. The at least one meso-scale or micro-scale resonator may be formed from a composite material. Additionally, the at least one meso-scale or micro-scale resonator may include a plurality of first carbon particles configured to uniquely resonate in response to an electromagnetic ping based at least in part on a concentration level of the first carbon particles within the at least one meso-scale or micro-scale resonator.

公开(公告)号：US20240275608A1

公开(公告)日：2024-08-15

申请号：US18440719

申请日：2024-02-13

Applicant: Lyten, Inc.

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

IPC: H04L9/32 ,  G02F1/167 ,  H04L9/40

CPC classification number: H04L9/3247 ,  G02F1/167 ,  H04L63/1416

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.

公开(公告)号：US20240273648A1

公开(公告)日：2024-08-15

申请号：US18440769

申请日：2024-02-13

Applicant: Lyten, Inc.

Inventor： Daniel Cook ,  Keith Norman ,  Kyle Matthys ,  Michael Stowell ,  Karel Vanheusden ,  George Clayton Gibbs ,  Jacques Nicole ,  Carlos Montalvo ,  Bruce Lanning ,  Sung Lim ,  John Chmiola

IPC: G06Q50/06 ,  G06Q30/018

CPC classification number: G06Q50/06 ,  G06Q30/018

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.

公开(公告)号：US20240264043A1

公开(公告)日：2024-08-08

申请号：US18596390

申请日：2024-03-05

Applicant: Lyten, Inc.

Inventor： Michael Stowell ,  Jacques Nicole ,  Carlos Montalvo ,  Daniel Cook

IPC: G01M17/02

CPC classification number: G01M17/02

Abstract: Resonant sensors for environmental health risk detection are disclosed. A mechanical member may include at least one meso-scale or micro-scale resonator disposed on a surface of the mechanical member. Additionally, the at least one meso-scale or micro-scale resonator may include a plurality of first carbon particles configured to uniquely resonate in response to an electromagnetic ping based at least in part on a concentration level of the first carbon particles within the at least one meso-scale or micro-scale resonator. Further, the at least one meso-scale or micro-scale resonator may be configured to resonate at a first frequency in response to the electromagnetic ping when the mechanical member is in a first state, and may be configured to resonate at a second frequency in response to the electromagnetic ping when the mechanical member is in a second state.

公开(公告)号：US11892372B2

公开(公告)日：2024-02-06

申请号：US18080606

申请日：2022-12-13

Applicant: Lyten, Inc.

Inventor： Michael Stowell ,  Carlos Montalvo ,  Jacques Nicole

IPC: G01M17/02 ,  G01B7/24 ,  B60C23/06 ,  B60C23/04 ,  B60C19/00 ,  G01B15/06

CPC classification number: G01M17/02 ,  B60C19/00 ,  B60C23/0493 ,  B60C23/064 ,  G01B7/24 ,  G01B15/06 ,  B60C2019/004

Abstract: A disclosed component may include at least one split-ring resonator, which may be embedded within a material. The split ring resonator may be formed from a three-dimensional (3D) monolithic carbonaceous growth and may detect an electromagnetic ping emitted from a user device. The split ring resonator may generate an electromagnetic return signal in response to the electromagnetic ping. The electromagnetic return signal may indicate a state of the material in a position proximate to a respective split ring resonator. In some aspects, the split-ring resonator may resonate at a first frequency in response to the electromagnetic ping when the material is in a first state, and may resonate at a second frequency in response to the electromagnetic ping when the material is in a second state. A resonant frequency of the 3D monolithic carbonaceous growth may be based on physical characteristics of the material.

公开(公告)号：US20250076233A1

公开(公告)日：2025-03-06

申请号：US18952878

申请日：2024-11-19

Applicant: Lyten, Inc.

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

IPC: G01N27/02 ,  G01N27/22 ,  G01N27/414 ,  G01N27/447 ,  G01N27/72 ,  G02F1/167 ,  G06Q30/018 ,  G06Q50/06 ,  H04L9/32 ,  H04L9/40

Abstract: Disclosed herein is a sensors-as-a-service ecosystem. In use, the system includes functions for receiving first sensor data at a sensors as a service platform, where the first sensor data corresponds to a first level of capabilities for a first sensor. The system also receives a selection of a sensor upgrade for the first sensor and provisions enhanced sensor capabilities for the sensor upgrade based on the selection. Furthermore, the system sends a sensor update with the enhanced sensor capabilities from the sensors as a service platform to the first sensor. Finally, the system receives second sensor data from the first sensor at the sensors as a service platform, where the second sensor data corresponds to a second level of capabilities for the first sensor.

公开(公告)号：US20250076154A1

公开(公告)日：2025-03-06

申请号：US18943655

申请日：2024-11-11

Applicant: Lyten, Inc.

Inventor： Michael Stowell ,  Jacques Nicole ,  Carlos Montalvo ,  Daniel Cook

IPC: G01M17/02

Abstract: Resonant sensors for environmental health risk detection are disclosed. A mechanical member may include at least one meso-scale or micro-scale resonator disposed on a surface of the mechanical member. Additionally, the at least one meso-scale or micro-scale resonator may include a plurality of first carbon particles configured to uniquely resonate in response to an electromagnetic ping based at least in part on a concentration level of the first carbon particles within the at least one meso-scale or micro-scale resonator. Further, the at least one meso-scale or micro-scale resonator may be configured to resonate at a first frequency in response to the electromagnetic ping when the mechanical member is in a first state, and may be configured to resonate at a second frequency in response to the electromagnetic ping when the mechanical member is in a second state.