MACHINERY FINGERPRINTING

• US 20130211662A1
• Filed: 02/11/2013
• Published: 08/15/2013
• Est. Priority Date: 02/09/2012
• Status: Active Grant

• Current Assignee: Vehcon, Inc.
• Original Assignee: Vehcon, Inc.
• Inventors: Blumer, Frederick T., Fuller, Joseph R.
• Granted Patent: US 9,170,982 B2
• Time in Patent Office: Days
• US Class Current: 701/31.4
• CPC Class Codes: G06F 17/00 Digital computing or data processing equipment or methods, specially adapted for specific functions information retrieval, database structures or file system structures therefor G06F16/00
• CPC Class Codes: G06F 2218/12 Classification; Matching
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 50/40 Business processes related to the transportation industry shipping G06Q10/083

Abstract

Disclosed are various embodiments for a fingerprinting application. Data and optionally additional metadata for an operational automobile are captured by an application executed on a mobile device inside the automobile. An fingerprinting application matches the data to known data profiles to confirm the identity or type of the automobile. Diagnostics of the automobile can be determined by variations in the data with respect to a defined standard. The data can include one or more of audio data, accelerometer data, vibration, data and orientation data.

Claims

1. A system, comprising:

at least one computing device; and

a fingerprinting application executable in the at least one computing device, the fingerprinting application comprising;

logic that obtains, from a mobile device, data generated by a motorized transportation device resulting from operation of the motorized transportation device;

logic that generates a profile as a function of the generated data; and

logic that determines whether the profile corresponds to at least one of a plurality of known profiles, each of the known profiles being associated with a particular motorized transportation device or type of motorized transportation device.

2. The system of claim 1, wherein the logic that determines further comprises:

logic that selects at least one of the known profiles;

logic that calculates a similarity between the generated profile and the selected at least one of the known profiles; and

wherein the determination is responsive to a criterion of similarity.

3. The system of claim 1, the fingerprinting application further comprising:

logic that applies a filter to the data to generate a plurality of data subsets; and

wherein the profiles and known profiles comprise data associated with each of the data subsets.

4. The system of claim 1, the fingerprinting application further comprising logic that applies a filter to the data to remove at least a portion of the data before generating the profile.

5. The system of claim 1, the system further comprises a data store storing a knowledge base of known profiles, and wherein the logic that determines further comprises logic that applies a supervised machine learning algorithm to the profile and the known profiles.

6. The system of claim 1, wherein the fingerprinting application further comprises:

logic that obtains metadata associated with the data; and

wherein the determining is performed as a function of the metadata.

7. The system of claim 6, wherein the metadata comprises at least one of location data of the mobile device, a weather condition, or a speed of the motorized transportation device at the time the data was generated.

8. The system of claim 1, wherein fingerprinting application further comprises:

logic that obtains data from the mobile device, the data selected from the group consisting of audio data, accelerometer data, vibration data, and combinations thereof; and

wherein the determining is performed as a function of the data.

9. The system of claim 1, wherein the fingerprinting application further comprises:

logic that, responsive to the determination, generates a variance or a measure of variance between the generated profile and the corresponding at least one of the known profiles; and

logic that generates a performance diagnosis for the motorized transportation device as a function of the variance or the measure of variance.

10. The system of claim 1, wherein the motorized transportation device is a vehicle, and the fingerprinting application further comprises:

logic that obtains a vehicle identification number (VIN) for the vehicle;

logic that obtains a vehicle configuration as a function of the VIN; and

wherein the determining is performed as a function of the vehicle configuration.

11. A method, comprising the steps of:

obtaining, by a computing device, from a mobile device, data comprising data generated by a motorized transportation device resulting from operation of the motorized transportation device;

generating, by the computing device, a profile as a function of the generated data; and

determining, by the computing device, whether the profile corresponds to at least one of a plurality of known profiles, each of the known profiles being associated with a particular motorized transportation device or type of motorized transportation device.

12. The method of claim 11, wherein the step of determining further comprises:

selecting, by the computing device, at least one of the known profiles;

calculating, by the computing device, a similarity between the generated profile and the selected at least one of the known profiles; and

wherein the determination is responsive to meeting a criterion of similarity.

13. The method of claim 11, further comprising the steps of:

applying, by the computing device, a filter to the data to generate a plurality of data subsets; and

wherein the profiles and known profiles comprise data associated with each of the data subsets.

14. The method of claim 11, further comprising the step of applying a filter to the data to remove at least a portion of the data before generating the profile.

15. The method of claim 11, further comprising:

maintaining, by the computing device, a knowledge base of the known profiles; and

wherein the step of determining further comprises applying a supervised machine learning algorithm to the profile and the known profiles.

16. The method of claim 11, further comprising:

obtaining, by the computing device, metadata associated with the data; and

wherein the determining is performed as a function of the metadata.

17. The method of claim 16, wherein the metadata comprises at least one of location data of the mobile device, a weather condition, or a speed of the motorized transportation device at the time the data was generated.

18. The method of claim 11, further comprising:

obtaining, by the computing device, data from the mobile device the data selected from the group consisting of audio data, accelerometer data, vibration data, and combinations thereof; and

wherein the step of determining is performed as a function of the data.

19. The method of claim 11, further comprising:

generating, by the computing device, responsive to the determination, a variance or a measure of variance between the generated profile and the corresponding at least one of the known profiles; and

generating, by the computing device, a performance diagnosis for the motorized transportation device as a function of the variance or the measure of variance.

20. The method of claim 11, wherein the motorized transportation device is a vehicle and the method further comprises:

obtaining, by the computing device, a vehicle identification number (VIN) for the vehicle;

obtaining, by the computing device, a vehicle configuration as a function of the VIN; and

wherein the determining is performed as a function of the vehicle configuration.