IP Library Granted Patent US 9,508,202
Granted Patent B2
US 9,508,202 · App. 14/957,301 · Granted Nov 29, 2016

Crowd sourced optimization of vehicle performance based on cloud based data

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Quick Facts
Patent No.
US 9,508,202
App. No.
14/957,301
Granted
Nov 29, 2016
Kind
B2
Abstract

Tracking intrinsic and extrinsic vehicle parameters for optimizing vehicle performance is presented herein. A method can include consolidating sets of data associated with a vehicle to generate a model; generating, using the model, recommendation data representing a recommendation associated with an operation of the vehicle; and in response to receiving a request from a device of the vehicle corresponding to the operation of the vehicle, sending, based on the request, a message comprising the recommendation directed to the device of the vehicle. In an example, the method can further include determining, based on crowdsourced data representing the characteristic of the element of the vehicle, whether the characteristic satisfies a defined condition with respect to the operation of the vehicle.

Claims (51)

1. A method, comprising:

based on crowdsourced data with respect to network based communications representing a characteristic of an element of a vehicle, generating, by a system comprising a processor, recommendation data representing a recommendation associated with an operation of the vehicle; and

in response to sending a message comprising the recommendation directed to a device of the vehicle, receiving, by the system, feedback data representing whether the recommendation has been implemented.

2. The method of claim 1 , further comprising:

consolidating, by the system, the crowdsourced data into a data structure representing a model that associates the characteristic with the recommendation.

3. The method of claim 2 , wherein the consolidating comprises:

receiving, from devices of vehicles comprising the vehicle, respective sensor data associated with the characteristic; and

generating the data structure using the respective sensor data.

4. The method of claim 2 , wherein the consolidating comprises:

receiving information representing a driving condition with respect to the operation of the vehicle; and

generating the data structure using the information representing the driving condition.

5. The method of claim 1 , further comprising:

receiving the network based communications from a group of devices via an Internet based interface; and

generating, by the system, a data structure representing a model using the crowdsourced data.

6. The method of claim 1 , wherein the generating the recommendation data comprises:

in response to receiving, from the device of the vehicle, sensor data representing the characteristic, determining, based on the sensor data, whether the characteristic satisfies a defined condition with respect to the operation of the vehicle.

7. The method of claim 1 , wherein the generating the recommendation data comprises:

in response to receiving information representing a driving condition with respect to the operation of the vehicle, determining, based on the information, whether the characteristic satisfies a defined condition with respect to the operation of the vehicle.

8. The method of claim 1 , wherein the generating the recommendation data comprises:

determining, based on the crowdsourced data, whether the characteristic satisfies a defined condition with respect to the operation of the vehicle.

9. The method of claim 8 , wherein the generating the recommendation data comprises:

in response to the characteristic being determined to satisfy the defined condition with respect to the operation of the vehicle, generating the recommendation data.

10. A system, comprising:

a processor, and

a memory that stores executable instructions that, when executed by the processor, facilitate performance of operations, comprising:

generating, based on data corresponding to network based communications representing a characteristic of an element of a vehicle, a recommendation with respect to an operation of the vehicle; and

in response to sending the recommendation directed to a device of the vehicle, receiving information indicating whether the recommendation has been applied.

11. The system of claim 10 , wherein the generating the recommendation comprises:

generating, based on the data, a model associating the characteristic of the element of the vehicle with the recommendation.

12. The system of claim 10 , wherein the operations further comprise:

receiving the data from respective devices via an Internet based interface.

13. The system of claim 10 , wherein the generating the recommendation comprises:

receiving, from the device of the vehicle, sensor data representing the characteristic; and

determining, based on the sensor data, whether the characteristic satisfies a defined condition with respect to the operation of the vehicle.

14. The system of claim 13 , wherein the determining comprises:

in response to determining, based on the sensor data, that the characteristic satisfies the defined condition with respect to the operation of the vehicle, performing the generating the recommendation.

15. The system of claim 10 , wherein the generating the recommendation comprises:

determining, based on the data, whether the characteristic satisfies a defined condition with respect to the operation of the vehicle.

16. The system of claim 15 , wherein the generating the recommendation comprises:

in response to determining, based on the data, that the characteristic satisfies the defined condition with respect to the operation of the vehicle, performing the generating the recommendation.

17. A machine-readable storage medium, comprising executable instructions that, when executed by a processor, facilitate performance of operations, comprising:

based on network based communications comprising respective data representing a characteristic of an element of a vehicle, creating a recommendation with respect to an operation of the vehicle; and

in response to sending the recommendation directed to a device of the vehicle, receiving feedback data representing whether the recommendation has been implemented.

18. The machine-readable storage medium of claim 17 , wherein the creating the recommendation comprises:

in response to determining, based on the respective data, that the characteristic satisfies a defined condition with respect to the operation of the vehicle, performing the creating the recommendation.

19. The machine-readable storage medium of claim 17 , wherein the creating the recommendation comprises:

receiving, from the device of the vehicle, sensor data representing the characteristic; and

in response to determining, based on the sensor data, that the characteristic satisfies a defined condition with respect to the operation of the vehicle, performing the creating the recommendation.

20. The computer-readable storage device of claim 17 , wherein the operations further comprise:

receiving, from devices of a group of vehicles comprising the vehicle, sets of sensor data associated with the characteristic of the element of the vehicle; and

creating a model using the sets of sensor data.

Assignments (4)
SECURITY INTEREST Recorded Nov 3, 2022
From: LYFT, INC.
To: JPMORGAN CHASE BANK, N.A., AS ADMINISTRATIVE AGENT
Reel/Frame 061880/0237 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 18, 2019
From: PROSPER TECHNOLOGY, LLC
To: LYFT, INC.
Reel/Frame 048097/0402 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 16, 2018
From: AT&T INTELLECTUAL PROPERTY I, L.P.
To: PROSPER TECHNOLOGY, LLC
Reel/Frame 046556/0096 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 2, 2015
From: MARATHE, NIKHIL S.; BALDWIN, CHRISTOPHER
To: AT&T INTELLECTUAL PROPERTY I, L.P.
Reel/Frame 037193/0734 →