Utilizing machine learning models and captured video of a vehicle to determine a valuation for the vehicle

Patent metadata

Field	Value
Publication number	US-11829946-B2
Application number	US-202117457771-A
Country	US
Kind code	B2
Filing date	Dec 6, 2021
Priority date	Mar 23, 2020
Publication date	Nov 28, 2023
Grant date	Nov 28, 2023

Abstract

A valuation platform may receive, from a user device, video data associated with a vehicle, and may receive a vehicle history report of the vehicle based on a vehicle identification number of the vehicle. The valuation platform may receive, from the user device, feature data associated with the vehicle, and may process the video data, the vehicle history report, and the feature data, with a machine learning model, to determine one or more values for the vehicle. The valuation platform may determine a valuation for the vehicle based on the determined one or more values for the vehicle. The valuation platform may create a vehicle profile for the vehicle based on the video data, the vehicle history report, the feature data, the determined one or more values for the vehicle, and the valuation for the vehicle, and may perform one or more actions based on the vehicle profile.

First claim

What is claimed is:

1. A method, comprising:
receiving, by a device and from a user device, video data identifying one or more conditions of a vehicle,
wherein receiving the video data is based on providing instructions via the user device to capture a series of vehicle features in operation, including:
a first video of activating and deactivating a first vehicle feature, and
a second video of a second vehicle feature in operation;

receiving, by the device, a vehicle history report of the vehicle based on a vehicle identification number of the vehicle;
receiving, by the device and from the user device, feature data associated with the vehicle;
processing, by the device, the video data, the vehicle history report, and the feature data, with a machine learning model, to determine one or more values for the vehicle,
wherein the machine learning model is trained based on historical video data, historical vehicle history reports, and historical feature data, and
wherein the machine learning model is trained based on:
performing an artificial neural network processing technique to perform pattern recognition with regard to patterns of the historical video data, the historical vehicle history reports, the historical feature data, and historical values,

wherein the machine learning model processes the first video of activating and deactivating the first vehicle feature and the second video of the second vehicle feature in operation to determine the one or more values for the vehicle;

determining, by the device and using a model, a valuation for the vehicle based on the one or more values for the vehicle,
wherein the model is configured to generate the valuation based on the one or more values for the vehicle and a historical range of values associated with historical sales information; and

creating, by the device, a vehicle profile for the vehicle based on the video data, the vehicle history report, the feature data, the one or more values for the vehicle, and the valuation for the vehicle.

2. The method of claim 1 , wherein the video data additionally comprises an image or a video of the vehicle identification number.

3. The method of claim 1 , further comprising:
performing optical character recognition on the video data to identify the vehicle identification number.

4. The method of claim 1 , wherein the feature data includes one or more of:
data identifying working features of the vehicle,
audio of an operating engine of the vehicle, or
data identifying tire treadwear of the vehicle.

5. The method of claim 1 , wherein processing the video data, the vehicle history report, and the feature data, with the machine learning model comprises:
processing the video data, the vehicle history report, and the feature data, with the machine learning model to create a range of values for the vehicle based on an exterior condition of the vehicle, an interior condition of the vehicle and the feature data.

6. The method of claim 1 , wherein determining the valuation for the vehicle comprises:
determining the valuation based on an average of the one or more values.

7. The method of claim 1 , wherein the vehicle profile identifies one or more of:
the video data,
the vehicle history report,
the feature data,
the one or more values, or
the valuation.

8. A device, comprising:
one or more memories; and
one or more processors, coupled to the one or more memories, configured to:
receive, from a user device, video data identifying one or more conditions of a vehicle,
wherein the video data is received based on providing instructions via the user device to capture a series of vehicle features in operation, including:
a first video of activating and deactivating a first vehicle feature, and
a second video of a second vehicle feature in operation;

receive a vehicle history report of the vehicle based on a vehicle identification number of the vehicle;
receive, from the user device, feature data associated with the vehicle;
process the video data, the vehicle history report, and the feature data, with one or more machine learning models, to determine one or more values for the vehicle,
wherein the one or more machine learning models are trained based on historical video data, historical vehicle history reports, or historical feature data, and
wherein the one or more machine learning models are trained based on:
performing an artificial neural network processing technique to perform pattern recognition with regard to patterns of the historical video data, the historical vehicle history reports, the historical feature data, and historical values;

determine, using a model, a valuation for the vehicle based on the one or more values for the vehicle,
wherein the model is configured to generate the valuation based on the one or more values for the vehicle and a historical range of values associated with historical sales information; and

create a vehicle profile for the vehicle based on the video data, the vehicle history report, the feature data, the one or more values for the vehicle, and the valuation for the vehicle.

9. The device of claim 8 , wherein the video data additionally comprises an image or a video of the vehicle identification number; and
wherein the one or more processors are further configured to:
perform an optical character recognition technique on the video data to identify the vehicle identification number.

10. The device of claim 8 , wherein the feature data includes one or more of:
audio of an operating engine of the vehicle, or
data identifying tire treadwear of the vehicle.

11. The device of claim 8 , wherein the one or more processors, to process the video data, the vehicle history report, and the feature data, with the one or more machine learning models, are configured to:
process the video data, with a first machine learning model, of the one or more machine learning models, to determine a condition of the vehicle.

12. The device of claim 11 , wherein the one or more processors, to process the video data, the vehicle history report, and the feature data, with the one or more machine learning models, are configured to:
process the feature data, with a second machine learning model, of the one or more machine learning models, to determine working features of the vehicle.

13. The device of claim 12 , wherein the one or more processors, to process the video data, the vehicle history report, and the feature data, with the one or more machine learning models, are configured to:
determine the one or more values based on the condition of the vehicle, and the working features.

14. The device of claim 8 , wherein the vehicle profile identifies information, images, and audio based on one or more of:
the video data,
the vehicle history report,
the feature data,
the one or more values, or
the valuation.

15. A non-transitory computer-readable medium storing a set of instructions, the set of instructions comprising:
one or more instructions that, when executed by one or more processors of a device, cause the device to:
receive, from a user device, video data identifying one or more conditions of a vehicle,
wherein the video data is received based on providing instructions via the user device to capture a series of vehicle features in operation, including:
a first video of activating and deactivating a first vehicle feature, and
a second video of a second vehicle feature in operation;

receive a vehicle history report of the vehicle based on a vehicle identification number of the vehicle;
receive, from the user device, feature data assoc

Assignees

• Capital One Services Llc

Inventors

• Tang Qiaochu
• Hoover Jason
• Price Micah
• Dagley Geoffrey
• Duckworth Staevan
• Youngblood Stewart

Classifications

• G06Q10/087 Primary

  Inventory or stock management, e.g. order filling, procurement or balancing against orders · CPC title

• G06F18/214

  Generating training patterns; Bootstrap methods, e.g. bagging or boosting · CPC title

• G06F18/217

  Validation; Performance evaluation; Active pattern learning techniques · CPC title

• G06N20/00

  Machine learning · CPC title

• G06Q10/10

  Office automation; Time management · CPC title