Vehicle data collection and verification

1. A system, comprising:

at least one computing device, configured to at least:

obtain, from a mobile device, a first at least one image capturing an image of at least a portion of a vehicle at a first point in time;

generate, from the first at least one image capturing an image of at least a portion of a vehicle, image data including an identifying feature of the vehicle;

verify that the vehicle of the first at least one image corresponds to a unique vehicle identification as a function of the image data of the first at least one image including an identifying feature of the vehicle by comparing the image data of the first image including an identifying feature of the vehicle to an image knowledge base, wherein the image knowledge base comprises an image depicting an identifying feature of the vehicle, and finding a match between the image depicting an identifying feature of the vehicle of the knowledge base and the image data of the first image including an identifying feature of the vehicle of the first at least one image of at least a portion of the vehicle; and

associate the image data including the identifying feature of the first at least one image with a single, unique vehicle.

2. The system of claim 1 , wherein the at least one computing device is further configured to:

generate from the first at least one image capturing an image of at least a portion of the vehicle image data a characteristic of the vehicle at a given location on the vehicle; and

associate the characteristic of the vehicle with the vehicle identification of a single, unique vehicle.

3. The system of claim 2 , wherein the characteristic of the vehicle is selected from the group consisting of a number of doors, a portion or section of the vehicle, vehicle color, vehicle markings, cleanliness of the vehicle, one or more parts of the vehicle, whether a part of the vehicle is missing, tinted windows, window and/or windshield condition, general vehicle condition, presence of rust, one or more dents, one or more scratches, the color of the interior of the vehicle, running board color, presence of a roof rack or other vehicle accessory, tire condition, the appearance of one or more of the wheel rims, wheels, hubcaps, and paint quality, and combinations thereof.

4. The system of claim 2 , wherein the characteristic is an odometer reading.

5. The system of claim 4 , wherein no change in the characteristic of the vehicle is determined between the first point in time and the second point in time.

6. The system of claim 4 , wherein a change in the characteristic of the vehicle is determined between the first point in time and the second point in time.

7. The system of claim 2 , wherein the at least one computing device is further configured to:

obtain, from a mobile device, a second at least one image capturing an image of the at least a portion of the vehicle captured in the first at least one image but at a second point in time subsequent to the first point in time;

generate, from the second at least one image capturing an image of the at least a portion of a vehicle, image data including an identifying feature of the vehicle and image data of a characteristic of the vehicle taken from the given location on the vehicle;

verify that the vehicle of the second at least one image corresponds to the unique vehicle identification as a function of the image data of the second image including an identifying feature of the vehicle by comparing the image data of the second at least one image including an identifying feature of the vehicle to an image knowledge base, wherein the image knowledge base comprises an image depicting an identifying feature of the vehicle, and finding a match between the image depicting an identifying feature of the vehicle of the knowledge base and the image data of the second image including an identifying feature of the vehicle of the second at least one image of the at least a portion of the vehicle; and

compare from the image data of a characteristic of the vehicle of the first at least one image of the at least a portion of the vehicle to the image data of a characteristic of the vehicle of the second at least one image of the at least a portion of the vehicle to determine whether or not there has been a change in the characteristic of the vehicle between the first point in time and the second point in time.

8. The system of claim 1 , wherein the image depicting an identifying feature of the vehicle of the knowledge base corresponds to a shared make, model or year of the vehicle.

9. The system of claim 1 , wherein the at least one computing device is further configured to associate the identifying feature with an account corresponding to the vehicle.

10. The system of claim 1 , wherein the at least one computing device is further configured to at least:

obtain, from the mobile device, operational data associated with a usage of the vehicle; and

associate the operational data with an account corresponding to the vehicle.

11. The system of claim 1 , wherein the at least one computing device is further configured to determine whether the first at least one image comprises altered or transformed image data.

12. The system of claim 1 , wherein comparing the image data of the first image of an identifying feature of the vehicle to the image knowledge base is performed based at least in part on a machine learning algorithm or an image matching algorithm.

13. A method comprising:

obtaining, by at least one computing device, from a mobile device, an image of at least a portion of a vehicle at a first point in time;

generating, from the image of at least a portion of the vehicle, by the at least one computing device, image data including an identifying feature of the vehicle;

verifying, by the at least one computing device, that the vehicle in the image obtained from the mobile device corresponds to a single, unique vehicle identification as a function of the image data generated from the image obtained from the mobile device including the identifying feature of the vehicle by comparing the image data including the identifying feature of the vehicle to an image knowledge base, wherein the image knowledge base comprises an image depicting an identifying feature of the vehicle, and finding a match between the identifying feature of the vehicle of the image in the knowledge base and the identifying feature of the vehicle included in the image data generated from the image obtained from the mobile device;

generating, by the at least one computing device, from the image of at least a portion of the vehicle or from a second image of at least a portion of the vehicle, image data including a characteristic of the vehicle;

associating the characteristic of the vehicle with the vehicle identification of the single, unique vehicle; and

storing the characteristic with respect to an account for the single, unique vehicle.

14. The method of claim 13 , wherein the image depicting an identifying feature of the vehicle of the knowledge base corresponds to a shared make, model or year of the vehicle.

15. The method of claim 13 , further comprising associating, by the at least one computing device, the identifying feature with an account corresponding to the vehicle.

16. The method of claim 13 , further comprising:

obtaining, by the at least one computing device, from the mobile device, operational data associated with a usage of the vehicle; and

associating, by the at least one computing device, the operational data with an account corresponding to the vehicle.

17. The method of claim 13 , further comprising determining, by the at least one computing device, whether the first at least one image comprises altered or transformed image data.

18. The method of claim 13 , wherein comparing the at least one image to the image knowledge base is performed based at least in part on a machine learning algorithm or an image matching algorithm.