Vehicle occupant data collection and processing with artificial intelligence

Patent metadata

Field	Value
Publication number	US-11163270-B2
Application number	US-201916507160-A
Country	US
Kind code	B2
Filing date	Jul 10, 2019
Priority date	Jul 10, 2019
Publication date	Nov 2, 2021
Grant date	Nov 2, 2021

Abstract

A server includes an interface, programmed to receive, from a vehicle, vehicle data indicative of vehicle status and user data indicative of usage of vehicle features by a user; and a processor, programmed to analyze the vehicle data and the user data using artificial intelligence (AI) logic to generate a comfort prediction for the user; and configure a comfort device associated with the user, external to the vehicle, using the comfort prediction.

First claim

What is claimed is:

1. A server, comprising:
an interface, programmed to receive, from a plurality of vehicles, vehicle data indicative of vehicle status and user data indicative of usage of vehicle features by a plurality of users; and
a processor, programmed to
analyze the vehicle data and the user data using artificial intelligence (AI) logic to generate an analysis result indicative of a comfort prediction for the users, a first vehicle feature of the vehicle features being more often used by vehicles at a first location, and a second vehicle feature of the vehicle features being more often used by vehicles at a second location;
configure a comfort device associated with the users, external to the vehicles, using the comfort prediction;
pushing a first software update version to vehicles at the first location to automatically activate the first feature; and
pushing a second software update version to vehicles at the second location to automatically activate the second feature.

2. The server of claim 1 , wherein the processor is further programmed to
query the vehicle data and the user data from the vehicle.

3. The server of claim 1 , wherein the user data further includes: a user anthropometric entry indicative of a weight and height of the user.

4. The server of claim 3 , wherein the user data further includes electroencephalography data of the user.

5. The server of claim 1 , wherein the vehicle data includes a seat dimension entry, a seat position entry, and a seat massage activation entry.

6. The server of claim 5 , wherein the vehicle data further includes at least one of: a vehicle vibration/damping entry, a heating, ventilation, and air conditioning entry, a vehicle mileage entry, a driving pattern entry, a road condition entry, a presence of booster seat entry, or a vehicle location entry.

7. The server of claim 1 , wherein the comfort prediction includes at least one of a seat position setting, a seat massage setting, or a heating, ventilation, and air conditioning setting.

8. The server of claim 7 , wherein the comfort device includes at least one of: a seat, or a building climate control system, and
the processor is further programmed to configure a second comfort device associated with the vehicle using the comfort prediction, the second comfort device being at least one of: a vehicle seat or a vehicle heating, ventilation, and air conditioning system.

9. The server of claim 1 , wherein the processor is further programmed to
detect the comfort device is available; and
responsive to verifying the comfort device is compatible with the comfort prediction, configure the comfort device using the comfort prediction.

10. The server of claim 1 , wherein the processor is further programmed to
analyze vehicle data and user data from multiple vehicles using the AI logic to generate an analysis result indicative a usage pattern of multiple vehicle features; and
select a version of software update based on the analysis result corresponding to the usage pattern of multiple vehicle features.

11. The server of claim 1 , wherein the processor is further programmed to
predict a warranty claim based on the analysis result.

12. A method for a server, comprising:
receiving, from multiple vehicles, vehicle data indicative of vehicle status and user data indicative of usage of vehicle features by multiple users;
analyzing the vehicle data and the user data using artificial intelligence (AI) logic to generate an analysis result indicative of a usage pattern of multiple vehicle features, wherein the usage pattern is indicative of a first vehicle feature of the vehicle features being more often used by vehicles at a first location, and a second vehicle feature of the vehicle features being more often used by vehicles at a second location;
pushing a first software update version to vehicles at the first location to automatically activate the first feature; and
pushing a second software update version to vehicles at the second location to automatically activate the second feature.

13. The method of claim 12 , further comprising:
predicting a warranty claim based on the analysis result.

14. The method of claim 12 , further comprising:
configuring a comfort device associated with at least one user, external to the vehicle using the analysis result.

15. The method of claim 14 , wherein the comfort device includes at least one of: a seat, or a building climate control system.

16. The method of claim 12 , further comprising:
configuring a second comfort device associated with the vehicle using the analysis result, the second comfort device being at least one of: a vehicle seat or a vehicle heating, ventilation, and air conditioning system.

17. A non-transitory computer-readable medium, comprising instructions that, when executed by a processor of a computer, cause the processor to:
query vehicles for vehicle data indicative of vehicle status and user data indicative of usage of vehicle features by multiple users;
responsive to receiving, from the vehicles, the vehicle data and the user data, analyze the vehicle data and the user data using artificial intelligence (AI) logic to generate an analysis result indicative a usage pattern of multiple vehicle features by the users, wherein the usage pattern is indicative of a first vehicle feature of the vehicle features being more often used by vehicles at a first location, and a second vehicle feature of the vehicle features being more often used by vehicles at a second location; and
output a warranty claim prediction based on the usage pattern of the multiple vehicle features.

18. The non-transitory computer-readable medium of claim 17 , further comprising instructions that, when executed by the processor of the computer, cause the processor to:
pushing a first software update version to vehicles at the first location to automatically activate the first feature; and
pushing a second software update version to vehicles at the second location to automatically activate the second feature.

19. The non-transitory computer-readable medium of claim 17 , wherein the analysis result is further indicative of a comfort prediction for at least one user,
the non-transitory computer-readable medium further comprising instructions, when executed by a processor of a computer, cause the computer to:
configure a comfort device associated with the user, external to the vehicles, using the comfort prediction.

20. The non-transitory computer-readable medium of claim 19 , wherein the comfort device includes at least one of: a seat, or a building climate control system.

Assignees

• Lear Corp

Inventors

• Migneco Francesco
• Gallagher David
• Weaver Mark
• Rimell Katie

Classifications

• G07C5/008

  communicating information to a remotely located station (transmission systems for measured values G08C) · CPC title

• H04W4/40

  for vehicles, e.g. vehicle-to-pedestrians [V2P] · CPC title

• G05B13/0265 Primary

  the criterion being a learning criterion · CPC title

• G06N20/00

  Machine learning · CPC title

• G07C5/085

  using electronic data carriers · CPC title