IP Library › Granted Patent US 12,340,536
Granted Patent B2
US 12,340,536 · App. 17/895,328 · Granted Jun 24, 2025

Systems and methods for managing assets

Inventors: Jerry Wagner (Chesterfield, VA); Michael Mossoba (Great Falls, VA); Joshua Edwards (Philadelphia, PA)
Assignee: CAPITAL ONE SERVICES, LLC
G06T7/73G06Q10/087G06T2207/10032G06T2207/30232
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Quick Facts
Patent No.
US 12,340,536
App. No.
17/895,328
Filed
Aug 25, 2022
Granted
Jun 24, 2025
Kind
B2
Examiner
ALAVI, AMIR
Art Unit
2668
USPC
382/103
Abstract

Disclosed embodiments may include a system for managing assets. The system may establish a connection with a drone comprising Light Detection and Ranging (LiDAR) sensors and an image capture device. The system may receive, via the drone, image data via the LiDAR sensors and the image capture device. The system may identify, from the image data via computer vision, one or more assets, a condition of the one or more assets, and a location associated with the one or more assets. The system may generate a dynamic report comprising the one or more assets, the condition of the one or more assets, and the location associated with the one or more assets.

Claims (49)

1. A system, comprising:

one or more processors; and

a memory in communication with the one or more processors and storing instructions that, when executed by the one or more processors, are configured to cause the system to:

establish a connection with a drone comprising Light Detection and Ranging (LiDAR) sensors and an image capture device;

receive, via the drone, image data via the LiDAR sensors and the image capture device, wherein the image data is based on an optimal resolution;

identify, from the image data via computer vision, one or more assets, a condition of the one or more assets, and a location associated with the one or more assets; and

generate a dynamic report comprising the one or more assets, the condition of the one or more assets, and the location associated with the one or more assets, the dynamic report further comprising a heat map corresponding to the optimal resolution.

2. The system of claim 1 , wherein the instructions are further configured to cause the system to:

identify, from the image data via computer vision, a lifespan of the one or more assets, an age of the one or more assets, or both.

3. The system of claim 1 , wherein the dynamic report further comprises a floorplan of the location associated with the one or more assets in a predetermined space, a three-dimensional map of the predetermined space, or combinations thereof.

4. The system of claim 1 , wherein the instructions are further configured to cause the system to:

determine whether the image data has not been received for a predetermined amount of time; and

responsive to determining the image data has not been received for a predetermined amount of time, transmit a notification to a computing device.

5. The system of claim 1 , wherein the drone is configured to determine, by a machine learning model (MLM), the optimal resolution associated with one or more objects in a predetermined space.

6. The system of claim 5 , wherein the drone is configured to optically and/or physically zoom in on the one or more objects based on determining the optimal resolution.

7. The system of claim 1 , wherein the instructions are further configured to cause the system to:

receive, via the drone, interaction data derived from at least one physical interaction between the drone and at least one object of one or more objects in a predetermined space.

8. The system of claim 7 , wherein the at least one object comprises an electronic lock, a button, a switch, or combinations thereof.

9. The system of claim 7 , wherein at least one physical interaction comprises the drone opening or closing the at least one object of the one or more objects in the predetermined space.

10. The system of claim 7 , wherein the interaction data comprises an indication of an amount of force needed to successfully manipulate the at least one object.

11. A system, comprising:

one or more processors; and

a memory in communication with the one or more processors and storing instructions that, when executed by the one or more processors, are configured to cause the system to:

establish a connection with a drone comprising Light Detection and Ranging (LiDAR) sensors and an image capture device;

receive, via the drone, image data via the LiDAR sensors and the image capture device, wherein the image data is based on an optimal resolution;

identify, from the image data via computer vision, one or more assets and a location associated with the one or more assets; and

generate a dynamic report comprising the one or more assets and the location associated with the one or more assets, the dynamic report further comprising a heat map corresponding to the optimal resolution.

12. The system of claim 11 , wherein the instructions are further configured to cause the system to:

identify, from the image data via computer vision, a lifespan of the one or more assets, an age of the one or more assets, a condition of the one or more assets, or combinations thereof.

13. The system of claim 11 , wherein the dynamic report further comprises a floorplan of the location associated with the one or more assets in a predetermined space, a three-dimensional map of the predetermined space, or both.

14. The system of claim 11 , wherein the instructions are further configured to cause the system to:

determine whether the image data has not been received for a predetermined amount of time; and

responsive to determining the image data has not been received for a predetermined amount of time, transmit a notification to a computing device.

15. The system of claim 11 , wherein the drone is configured to determine, by a machine learning model (MLM), an optimal resolution associated with one or more objects in a predetermined space.

16. The system of claim 15 , wherein the drone is configured to optically and/or physically zoom in on the one or more objects based on determining the optimal resolution.

17. A drone, comprising:

one or more processors; and

a memory in communication with the one or more processors and storing instructions that, when executed by the one or more processors, are configured to cause the drone to:

establish a connection with a server;

detect, via Light Detection and Ranging (LiDAR) sensors and an image capture device, one or more objects in a predetermined space;

determine, by a machine learning model (MLM), an optimal resolution associated with each of the one or more objects;

obtain interaction data by physically interacting with at least one object of the one or more objects in the predetermined space; and

transmit, to the server and via the LiDAR sensors and the image capture device, image data corresponding to the one or more objects and based on the optimal resolution and the interaction data.

18. The drone of claim 17 , wherein the at least one object comprises an electronic lock, a button, a switch, or combinations thereof.

19. The drone of claim 17 , wherein the instructions are further configured to cause the drone to:

responsive to determining the optimal resolution, optically and/or physically zoom in on the one or more objects in the predetermined space.

20. The drone of claim 17 , wherein the instructions are further configured to cause the drone to:

determine whether at least one object of the one or more objects in the predetermined space is inaccessible; and

responsive to determining the at least one object is inaccessible, transmit a notification to the server.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 25, 2022
From: WAGNER, JERRY; MOSSOBA, MICHAEL; EDWARDS, JOSHUA
To: CAPITAL ONE SERVICES, LLC
Reel/Frame 060898/0398 →
Continuity (1)
Related Publication 20240070899A1 · Feb 29, 2024
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