Systems and methods for using spatial and temporal analysis to associate data sources with mobile devices

• US 9,565,522 B2
• Filed: 02/17/2016
• Issued: 02/07/2017
• Est. Priority Date: 10/09/2013
• Status: Active Grant

• Current Assignee: Mobile Design Technologies Incorporated
• Original Assignee: Mobile Technology Corporation, LLC
• Inventors: Hartzell, Dale, Welton, Mark, Perri, Michael
• Primary Examiner(s): DOAN, KIET M
• Application Number:
  US15/046,375
• Publication Number:
  US 20160165389A1
• Time in Patent Office: 356 Days
• Field of Search: 455/456.3, 455/452.2, 455/456.1, 455/404.2, 455/456.5, 455/414.2, 370/328, 707/709, 701/408, 701/207, 701/461
• US Class Current: 1/1
• CPC Class Codes: G06Q 30/0205 Location or geographical consideration
• CPC Class Codes: G06Q 30/0261 based on user location
• CPC Class Codes: G06Q 30/0277 Online advertisement
• CPC Class Codes: G06Q 50/01 Social networking
• CPC Class Codes: H04L 67/535 Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34
• CPC Class Codes: H04W 12/02 Protecting privacy or anonymity, e.g. protecting personally identifiable information [PII]
• CPC Class Codes: H04W 12/50 Secure pairing of devices
• CPC Class Codes: H04W 4/02 Services making use of location information
• CPC Class Codes: H04W 4/023 using mutual or relative location information between multiple location based services [LBS] targets or of distance thresholds
• CPC Class Codes: H04W 4/029 Location-based management or tracking services
• CPC Class Codes: H04W 4/21 for social networking applications

Abstract

Various embodiments of the present technology generally relate to data delivery. More specifically, some embodiments of the present technology relate to systems and methods for using spatial and temporal analysis to associate data sources with mobile devices. The delivery of data to support a wide variety of services for and about mobile devices that are based on data stored in corporate, commercial, and government databases which is not currently linked to individual mobile devices. Some embodiments allow advertisers to better target their ads to relevant target audience with greater accuracy.

Claims

1. A method of associating a mobile device to a household, the method comprising:

receiving a plurality of latitude-longitude pairs for a mobile device, the latitude-longitude pairs corresponding to a location of the mobile device during a time period;

organizing the plurality of latitude-longitude pairs into a plurality of clusters, the clusters corresponding to geographic regions visited by the mobile device during the time period;

calculating a score for each cluster, the score representing a likelihood that a user of the mobile device resides in a household within the cluster;

identifying a location of the user'"'"'s household, the location corresponding to the cluster having the highest score; and

associating the mobile device with the user'"'"'s household.

2. The method of claim 1, wherein the latitude-longitude pairs are obtained using a technique selected from the group consisting of global positioning with a global positioning system, cellular triangulation, and/or WiFi identification.

3. The method of claim 1, wherein the time period is selected from an hour, a day, a week, or a month.

4. The method of claim 1, wherein the mobile device is selected from a cellular phone, a portable computing device, and a tablet computer.

5. The method of claim 1, wherein the latitude-longitude pairs are associated with an ad request sent by the mobile device.

6. The method of claim 1, wherein calculating the score comprises applying a weight based on at least one of a time and a location associated with a longitude-latitude pair.

7. The method of claim 6, wherein the weight is based on the time associated with the latitude-longitude pair, according to a likelihood that the mobile device was in the household at the time.

8. The method of claim 6, wherein the weight is based on the location associated with the latitude-longitude pair, according to a likelihood that the location corresponds to a residential location.

9. The method of claim 1, further comprising rejecting a latitude-longitude pair based on an indication that the latitude-longitude pair is erroneous.

10. The method of claim 1, further comprising:

receiving, during a second time period, a plurality of second latitude-longitude pairs for the mobile device, the second latitude-longitude pairs corresponding to a location of the mobile device during the second time period;

organizing the plurality of second latitude-longitude pairs into a plurality of second clusters, the second clusters corresponding to geographic regions visited by the mobile device during the second time period;

calculating a second score for each second cluster, the second score representing a likelihood that the user of the mobile device resides in a household within the second cluster; and

identifying a second location of the user'"'"'s household, the second location corresponding to the second cluster having the highest second score.

11. The method of claim 10, further comprising performing a state update, the state update comprising:

determining whether the location of the user'"'"'s household and the second location of the user'"'"'s household are consistent;

if the location and the second location are consistent, determining a revised location of the user'"'"'s household as a function of the location and the second location;

if (i) the location and the second location are not consistent, and (ii) the highest second score is less than or equal to the highest score, associating the mobile device with the location; and

if (i) the location and the second location are not consistent, and (ii) the highest second score is greater than the highest score, associating the mobile device with the second location of the user'"'"'s household.

12. The method of claim 1, further comprising assigning statistical metrics to measure fitness of the device ID and household ID association.

13. A system for associating a mobile device to a household, the system comprising:

a data storage device operating on a server computer, the data storage device storing a plurality of latitude-longitude pairs for a mobile device, the latitude-longitude pairs corresponding to a location of the mobile device during a time period; and

a processor for executing computer-readable instructions that, when executed;

organize the plurality of latitude-longitude pairs into a plurality of clusters, the clusters corresponding to geographic regions visited by the mobile device during the time period;

calculate a score for each cluster, the score representing a likelihood that a user of the mobile device resides in a household within the cluster;

identify a location of the user'"'"'s household, the location corresponding to the cluster having the highest score; and

associate the mobile device with the user'"'"'s household.

14. The system of claim 13, wherein the latitude-longitude pairs are obtained using a technique selected from the group consisting of global positioning with a global positioning system, cellular triangulation, and/or WiFi identification.

15. The system of claim 13, wherein the time period is selected from an hour, a day, a week, or a month.

16. The system of claim 13, wherein the mobile device is selected from a cellular phone, a portable computing device, and a tablet computer.

17. The system of claim 13, wherein the latitude-longitude pairs are associated with an ad request sent by the mobile device.

18. The system of claim 13, wherein calculating the score comprises applying a weight based on at least one of a time and a location associated with a longitude-latitude pair.

19. The system of claim 18, wherein the weight is based on the time associated with the latitude-longitude pair, according to a likelihood that the mobile device was in the household at the time.

20. The system of claim 18, wherein the weight is based on the location associated with the latitude-longitude pair, according to a likelihood that the location corresponds to a residential location.

21. The system of claim 13, wherein the computer-readable instructions, when executed, further reject a latitude-longitude pair based on an indication that the latitude-longitude pair is erroneous.

22. The system of claim 13, wherein the computer-readable instructions, when executed:

receive, during a second time period, a plurality of second latitude-longitude pairs for the mobile device, the second latitude-longitude pairs corresponding to a location of the mobile device during the second time period;

organize the plurality of second latitude-longitude pairs into a plurality of second clusters, the second clusters corresponding to geographic regions visited by the mobile device during the second time period;

calculate a second score for each second cluster, the second score representing a likelihood that the user of the mobile device resides in a household within the second cluster; and

identify a second location of the user'"'"'s household, the second location corresponding to the second cluster having the highest second score.

23. The system of claim 22, wherein the computer-readable instructions, when executed, perform a state update comprising:

determining whether the location of the user'"'"'s household and the second location of the user'"'"'s household are consistent;

if the location and the second location are consistent, determining a revised location of the user'"'"'s household as a function of the location and the second location;

if (i) the location and the second location are not consistent, and (ii) the highest second score is less than or equal to the highest score, associating the mobile device with the location; and

if (i) the location and the second location are not consistent, and (ii) the highest second score is greater than the highest score, associating the mobile device with the second location of the user'"'"'s household.

24. The system of claim 13, wherein the computer-readable instructions, when executed, assign statistical metrics to measure fitness of the device ID and household ID association.

25. A computer program product embodied on a non-transitory computer-readable medium and comprising computer code for associating a mobile device to a household, the code comprising instructions stored in a data storage medium and executable on a processing device;

and, when executed by the processing device, the processing device;

receives a plurality of latitude-longitude pairs for a mobile device, the latitude-longitude pairs corresponding to a location of the mobile device during a time period;

organizes the plurality of latitude-longitude pairs into a plurality of clusters, the clusters corresponding to geographic regions visited by the mobile device during the time period;

calculates a score for each cluster, the score representing a likelihood that a user of the mobile device resides in a household within the cluster;

identifies a location of the user'"'"'s household, the location corresponding to the cluster having the highest score; and

associates the mobile device with the user'"'"'s household.