MLchartDataset catalogue

Patent · US12339934B1 · B1 · US

Systems and methods of sensor data fusion

(11) Publication number
US12339934B1
(21) Application number
19/081,688
(22) Filing date
2025-03-17
(30) Priority date
2024-12-19
(43) Publication date
2025-06-24
(45) Date of grant
2025-06-24
(51) IPC
G06F 18/21; G06F 18/25
(52) CPC
  • G06F Electric digital data processing: 18/256, 16/24, 16/245, 16/2455, 16/24556, 16/2456, 16/33, 16/334, 16/43, 16/53, 16/903, 16/90335, 16/9035, 17/18, 18/213, 18/217, 18/2431, 18/25, 18/251, 18/253, 7/14, 7/16
  • B25J Manipulators; chambers provided with manipulation devices: 9/163, 9/1664, 9/1694
  • B60R Vehicles, vehicle fittings, or vehicle parts, not otherwise provided for: 19/483
  • B60T Vehicle brake control systems or parts thereof; brake control systems or parts thereof, in general; arrangement of braking elements on vehicles in general; portable devices for preventing unwanted movement of vehicles; vehicle modifications to facilitate cooling of brakes: 2201/00, 2201/03, 8/1755, 8/3275
  • B60W Conjoint control of vehicle sub-units of different type or different function; control systems specially adapted for hybrid vehicles; road vehicle drive control systems for purposes not related to the control of a particular sub-unit: 10/18, 10/184, 2050/0052, 2050/021, 2050/0215, 2050/022, 2420/00, 2420/40, 2420/403, 2420/408, 2420/50, 2510/069, 2510/18, 2520/04, 2540/12, 2554/801, 2554/802, 2556/35, 2710/18, 2754/30, 30/085, 30/09, 60/00, 60/0018, 60/00186
  • B62D Motor vehicles; trailers: 15/0285
  • G01C Measuring distances, levels or bearings; surveying; navigation; gyroscopic instruments; photogrammetry or videogrammetry: 21/165, 21/1652, 21/3804, 21/3811, 21/3848, 22/00, 3/00
  • G01S Radio direction-finding; radio navigation; determining distance or velocity by use of radio waves; locating or presence-detecting by use of the reflection or reradiation of radio waves; analogous arrangements using other waves: 11/00, 13/08, 13/103, 13/42, 13/86, 13/862, 13/865, 13/867, 13/881, 13/931, 15/08, 15/101, 15/42, 17/08, 17/86, 17/87, 17/88, 17/89, 17/894, 17/931, 19/45, 2013/93185, 5/14, 7/417, 7/4808
  • G05B Control or regulating systems in general; functional elements of such systems; monitoring or testing arrangements for such systems or elements: 13/0205
  • G05D Systems for controlling or regulating non-electric variables: 2101/15, 2111/50, 2111/67
  • G06N Computing arrangements based on specific computational models: 20/00, 3/02, 3/0464, 5/022, 5/04, 5/042, 5/045, 5/046, 5/048
  • G06T Image data processing or generation, in general: 2207/10028, 2207/20024, 2207/20084, 2207/30252, 2207/30264, 7/521
  • G06V Image or video recognition or understanding: 10/764, 10/80, 10/803, 10/82, 20/56, 20/58
  • G08B Signalling systems, e.g. personal calling systems; order telegraphs; alarm systems: 29/188
  • G08G Traffic control systems: 1/0133, 1/04, 1/042
  • H04L Transmission of digital information, e.g. telegraphic communication: 67/12
  • H04W Wireless communication networks: 4/38
(73) Assignee
Digital Global Systems Inc
(72) Inventors
Armando Montalvo
(54) Title
Systems and methods of sensor data fusion
(57) Abstract

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

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Claims (20)

  1. A system for sensor data fusion for sensor management and utilization, comprising: at least one computer processor including a memory; at least one curation engine, at least one link engine, at least one fusion engine, at least one inference engine, and at least one validation engine; at least one first sensor of a first sensor type, operable to measure a first parameter of an environment and/or a machine; and at least one second sensor of a second sensor type, operable to measure a second parameter of the environment and/or the machine; wherein the at least one computer processor is operable to analyze data relating to the first parameter and the second parameter; wherein the at least one curation engine is operable to curate the first parameter and the second parameter, the at least one link engine is operable to link the first parameter and the second parameter, the at least one fusion engine is operable to fuse the first parameter and the second parameter, the at least one inference engine is operable to determine at least one inference from the first parameter and the second parameter, and the at least one validation engine is operable to validate the first parameter and the second parameter via validating the at least one inference; wherein the at least one validation engine is operable to determine a second inference; and wherein the at least one validation engine validates the at least one inference when a comparison between the at least one inference and the second inference exceeds a predefined threshold.
  2. The system of claim 1, wherein the at least one first sensor and/or the at least one second sensor includes an accelerometer, a gyroscope, a force/torque sensor, a proximity sensor, a gear sensor, a magnetic sensor, a humidity sensor, an angle sensor, a temperature sensor, a 6-axis combo inertial sensor, a current sensor, a Light Detection and Ranging (LiDAR) sensor, radar sensor, ultrasonic sensor, visible spectrum camera, Global Positioning System (GPS) sensor, inertial measurement unit, infrared sensor, depth camera, load sensor, a thermal power sensor, a diode detector, and/or a spectrometer.
  3. The system of claim 1, wherein the system is operable to store the first parameter and the second parameter after the at least one validation engine validates the at least one inference.
  4. The system of claim 1, wherein the at least one validation engine is operable to validate the at least one inference passively and/or actively.
  5. The system of claim 4, wherein passive validation includes not modifying a parameter.
  6. The system of claim 4, wherein active validation includes modifying at least one parameter.
  7. The system of claim 1, wherein the at least one validation engine is operable to use artificial intelligence to dynamically adjust the predefined threshold based in part on types of data sources, environmental factors, and/or learning from previous analyses conducted by the at least one validation engine.
  8. A method for sensor data fusion for sensor management and utilization, comprising: providing at least one computer processor including a memory; providing at least one curation engine, at least one link engine, at least one fusion engine, at least one inference engine, and at least one validation engine; at least one first sensor, being of a first sensor type, measuring a first parameter of an environment and/or a machine; at least one second sensor, being of a second sensor type, measuring a second parameter of the environment and/or the machine; analyzing by the at least one computer processor the first parameter and the second parameter; curating the first parameter and the second parameter via the at least one curation engine, linking the first parameter and the second parameter via the at least one link engine, fusing the first parameter and the second parameter via the at least one fusion engine, determining at least one inference from the first parameter and the second parameter via the at least one inference engine, and validating the first parameter and the second parameter via the at least one validation engine by validating the at least one inference; determining via the at least one validation engine a second inference; and validating via the at least one validation engine the at least one inference when a comparison between the at least one inference and the second inference exceeds a predefined threshold.
  9. The method of claim 8, wherein the at least one first sensor and/or the at least one second sensor includes an accelerometer, a gyroscope, a force/torque sensor, a proximity sensor, a gear sensor, a magnetic sensor, a humidity sensor, an angle sensor, a temperature sensor, a 6-axis combo inertial sensor, a current sensor, a Light Detection and Ranging (LiDAR) sensor, radar sensor, ultrasonic sensor, visible spectrum camera, Global Positioning System (GPS) sensor, inertial measurement unit, infrared sensor, depth camera, load sensor, a thermal power sensor, a diode detector, and/or a spectrometer.
  10. The method of claim 8, further comprising validating the at least one inference passively and/or actively.
  11. The method of claim 10, wherein validating passively includes not modifying a parameter.
  12. The method of claim 10, wherein validating actively includes modifying at least one parameter.
  13. The method of claim 8, further comprising adjusting via the at least one validation engine using artificial intelligence the predefined threshold based in part on types of data sources, environmental factors, and/or learning from previous analyses conducted by the at least one validation engine.
  14. The method of claim 8, further comprising storing the first parameter and the second parameter after the at least one validation engine validates the at least one inference.
  15. A system for sensor data fusion for sensor management and utilization, comprising: at least one computer processor including a memory; at least one curation engine, at least one link engine, at least one fusion engine, at least one inference engine, and at least one validation engine; at least one first sensor, being of a first sensor type, operable to measure a first parameter of an environment and/or a machine; and at least one second sensor, being of a second sensor type, operable to measure a second parameter of the environment and/or the machine; wherein the at least one computer processor is operable to analyze the first parameter and the second parameter; wherein the at least one curation engine is operable to curate the first parameter and the second parameter, the at least one link engine is operable to link the first parameter and the second parameter, the at least one fusion engine is operable to fuse the first parameter and the second parameter, the at least one inference engine is operable to determine at least one inference from the first parameter and the second parameter, and the at least one validation engine is operable to validate the first parameter and the second parameter via validating the at least one inference; wherein the at least one validation engine is operable to determine a second inference; wherein the at least one validation engine validates the at least one inference when a comparison between the at least one inference and the second inference exceeds a predefined threshold; and wherein the at least one validation engine is operable to use artificial intelligence to dynamically adjust the predefined threshold.
  16. The system of claim 15, wherein the at least one first sensor and/or the at least one second sensor includes an accelerometer, a gyroscope, a force/torque sensor, a proximity sensor, a gear sensor, a magnetic sensor, a humidity sensor, an angle sensor, a temperature sensor, a 6-axis combo inertial sensor, a current sensor, a Light Detection and Ranging (LiDAR) sensor, radar sensor, ultrasonic sensor, visible spectrum camera, Global Positioning System (GPS) sensor, inertial measurement unit, infrared sensor, depth camera, load sensor, a thermal power sensor, a diode detector, and/or a spectrometer.
  17. The system of claim 15, wherein the at least one validation engine is operable to validate the at least one inference passively and/or actively.
  18. The system of claim 17, wherein passive validation includes not modifying a parameter.
  19. The system of claim 17, wherein active validation includes modifying at least one parameter.
  20. The system of claim 15, wherein the system is operable to store the first parameter and the second parameter after the at least one validation engine validates the at least one inference.

Description

The present invention relates to physical sensors measuring data and dynamically fusing the physical sensor data to create a new dataset.

It is generally known in the prior art to append data from more than one source.

Prior art patent documents include the following:

U.S. Patent Publication Number 2024/0378412 for methods for topological data analysis ai/ml pipeline (tdaml) with algorithm for multimodal sensor data fusion in autonomy applications, by inventor Paul Thomas Schrader, filed Apr. 25, 2024, published Nov. 14, 2024, directed to a method of topological data analysis feature engineering for data fusion and autonomy is provided. The method comprises providing a Topological Data Analysis AI/ML Pipeline (TDAML) algorithm for multimodal sensor data fusion in autonomy applications system further comprising combining raw heterogeneous multimodal sensor data at the topological level; measuring, recording, and tracking linear representations of an underlying data set; providing a linear representation of the underlying data set which is compatible to existing deep learning (DL) model architectures for training in autonomy tasks; and accessing the entire degree of freedom (DOF) space of raw multimodal sensor data for mitigating sensor modality adversarial threats and environmental attenuation concerns in contested military and civilian (urban) environments.

U.S. Patent Publication Number 2023/0112441 for data fusion and analysis engine for vehicle sensors, by inventors LuAn Tang et al., filed Oct. 6, 2022, published Apr.

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Record as JSON 
{
  "publication_number": "US12339934B1",
  "country": "US",
  "kind": "B1",
  "title": "Systems and methods of sensor data fusion",
  "abstract": "Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.",
  "claims": [
    "1. A system for sensor data fusion for sensor management and utilization, comprising: at least one computer processor including a memory; at least one curation engine, at least one link engine, at least one fusion engine, at least one inference engine, and at least one validation engine; at least one first sensor of a first sensor type, operable to measure a first parameter of an environment and/or a machine; and at least one second sensor of a second sensor type, operable to measure a second parameter of the environment and/or the machine; wherein the at least one computer processor is operable to analyze data relating to the first parameter and the second parameter; wherein the at least one curation engine is operable to curate the first parameter and the second parameter, the at least one link engine is operable to link the first parameter and the second parameter, the at least one fusion engine is operable to fuse the first parameter and the second parameter, the at least one inference engine is operable to determine at least one inference from the first parameter and the second parameter, and the at least one validation engine is operable to validate the first parameter and the second parameter via validating the at least one inference; wherein the at least one validation engine is operable to determine a second inference; and wherein the at least one validation engine validates the at least one inference when a comparison between the at least one inference and the second inference exceeds a predefined threshold.",
    "2. The system of claim 1, wherein the at least one first sensor and/or the at least one second sensor includes an accelerometer, a gyroscope, a force/torque sensor, a proximity sensor, a gear sensor, a magnetic sensor, a humidity sensor, an angle sensor, a temperature sensor, a 6-axis combo inertial sensor, a current sensor, a Light Detection and Ranging (LiDAR) sensor, radar sensor, ultrasonic sensor, visible spectrum camera, Global Positioning System (GPS) sensor, inertial measurement unit, infrared sensor, depth camera, load sensor, a thermal power sensor, a diode detector, and/or a spectrometer.",
    "3. The system of claim 1, wherein the system is operable to store the first parameter and the second parameter after the at least one validation engine validates the at least one inference.",
    "4. The system of claim 1, wherein the at least one validation engine is operable to validate the at least one inference passively and/or actively.",
    "5. The system of claim 4, wherein passive validation includes not modifying a parameter.",
    "6. The system of claim 4, wherein active validation includes modifying at least one parameter.",
    "7. The system of claim 1, wherein the at least one validation engine is operable to use artificial intelligence to dynamically adjust the predefined threshold based in part on types of data sources, environmental factors, and/or learning from previous analyses conducted by the at least one validation engine.",
    "8. A method for sensor data fusion for sensor management and utilization, comprising: providing at least one computer processor including a memory; providing at least one curation engine, at least one link engine, at least one fusion engine, at least one inference engine, and at least one validation engine; at least one first sensor, being of a first sensor type, measuring a first parameter of an environment and/or a machine; at least one second sensor, being of a second sensor type, measuring a second parameter of the environment and/or the machine; analyzing by the at least one computer processor the first parameter and the second parameter; curating the first parameter and the second parameter via the at least one curation engine, linking the first parameter and the second parameter via the at least one link engine, fusing the first parameter and the second parameter via the at least one fusion engine, determining at least one inference from the first parameter and the second parameter via the at least one inference engine, and validating the first parameter and the second parameter via the at least one validation engine by validating the at least one inference; determining via the at least one validation engine a second inference; and validating via the at least one validation engine the at least one inference when a comparison between the at least one inference and the second inference exceeds a predefined threshold.",
    "9. The method of claim 8, wherein the at least one first sensor and/or the at least one second sensor includes an accelerometer, a gyroscope, a force/torque sensor, a proximity sensor, a gear sensor, a magnetic sensor, a humidity sensor, an angle sensor, a temperature sensor, a 6-axis combo inertial sensor, a current sensor, a Light Detection and Ranging (LiDAR) sensor, radar sensor, ultrasonic sensor, visible spectrum camera, Global Positioning System (GPS) sensor, inertial measurement unit, infrared sensor, depth camera, load sensor, a thermal power sensor, a diode detector, and/or a spectrometer.",
    "10. The method of claim 8, further comprising validating the at least one inference passively and/or actively.",
    "11. The method of claim 10, wherein validating passively includes not modifying a parameter.",
    "12. The method of claim 10, wherein validating actively includes modifying at least one parameter.",
    "13. The method of claim 8, further comprising adjusting via the at least one validation engine using artificial intelligence the predefined threshold based in part on types of data sources, environmental factors, and/or learning from previous analyses conducted by the at least one validation engine.",
    "14. The method of claim 8, further comprising storing the first parameter and the second parameter after the at least one validation engine validates the at least one inference.",
    "15. A system for sensor data fusion for sensor management and utilization, comprising: at least one computer processor including a memory; at least one curation engine, at least one link engine, at least one fusion engine, at least one inference engine, and at least one validation engine; at least one first sensor, being of a first sensor type, operable to measure a first parameter of an environment and/or a machine; and at least one second sensor, being of a second sensor type, operable to measure a second parameter of the environment and/or the machine; wherein the at least one computer processor is operable to analyze the first parameter and the second parameter; wherein the at least one curation engine is operable to curate the first parameter and the second parameter, the at least one link engine is operable to link the first parameter and the second parameter, the at least one fusion engine is operable to fuse the first parameter and the second parameter, the at least one inference engine is operable to determine at least one inference from the first parameter and the second parameter, and the at least one validation engine is operable to validate the first parameter and the second parameter via validating the at least one inference; wherein the at least one validation engine is operable to determine a second inference; wherein the at least one validation engine validates the at least one inference when a comparison between the at least one inference and the second inference exceeds a predefined threshold; and wherein the at least one validation engine is operable to use artificial intelligence to dynamically adjust the predefined threshold.",
    "16. The system of claim 15, wherein the at least one first sensor and/or the at least one second sensor includes an accelerometer, a gyroscope, a force/torque sensor, a proximity sensor, a gear sensor, a magnetic sensor, a humidity sensor, an angle sensor, a temperature sensor, a 6-axis combo inertial sensor, a current sensor, a Light Detection and Ranging (LiDAR) sensor, radar sensor, ultrasonic sensor, visible spectrum camera, Global Positioning System (GPS) sensor, inertial measurement unit, infrared sensor, depth camera, load sensor, a thermal power sensor, a diode detector, and/or a spectrometer.",
    "17. The system of claim 15, wherein the at least one validation engine is operable to validate the at least one inference passively and/or actively.",
    "18. The system of claim 17, wherein passive validation includes not modifying a parameter.",
    "19. The system of claim 17, wherein active validation includes modifying at least one parameter.",
    "20. The system of claim 15, wherein the system is operable to store the first parameter and the second parameter after the at least one validation engine validates the at least one inference."
  ],
  "description_excerpt": "The present invention relates to physical sensors measuring data and dynamically fusing the physical sensor data to create a new dataset.\n\nIt is generally known in the prior art to append data from more than one source.\n\nPrior art patent documents include the following:\n\nU.S. Patent Publication Number 2024/0378412 for methods for topological data analysis ai/ml pipeline (tdaml) with algorithm for multimodal sensor data fusion in autonomy applications, by inventor Paul Thomas Schrader, filed Apr. 25, 2024, published Nov. 14, 2024, directed to a method of topological data analysis feature engineering for data fusion and autonomy is provided. The method comprises providing a Topological Data Analysis AI/ML Pipeline (TDAML) algorithm for multimodal sensor data fusion in autonomy applications system further comprising combining raw heterogeneous multimodal sensor data at the topological level; measuring, recording, and tracking linear representations of an underlying data set; providing a linear representation of the underlying data set which is compatible to existing deep learning (DL) model architectures for training in autonomy tasks; and accessing the entire degree of freedom (DOF) space of raw multimodal sensor data for mitigating sensor modality adversarial threats and environmental attenuation concerns in contested military and civilian (urban) environments.\n\nU.S. Patent Publication Number 2023/0112441 for data fusion and analysis engine for vehicle sensors, by inventors LuAn Tang et al., filed Oct. 6, 2022, published Apr.",
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  "assignees": [
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  "inventors": [
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  "filing_date": "2025-03-17",
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  "priority_date": "2024-12-19",
  "application_number": "US-202519081688-A",
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Record 163 of 8,000 in Patents full text (MLC-0201). Request the full dataset.