Generating and Tracking Activity Patterns for Mobile Devices

• US 20110022312A1
• Filed: 07/23/2009
• Published: 01/27/2011
• Est. Priority Date: 07/23/2009
• Status: Abandoned Application

• Current Assignee: FMR LLC
• Original Assignee: FMR LLC
• Inventors: Stern, Hadley Rupert, McDonough, John C.
• Application Number:
  US12/508,509
• Publication Number:
  US 20110022312A1
• Time in Patent Office: Days
• US Class Current: 701/209
• CPC Class Codes: G01C 21/20 Instruments for performing navigational calculations G01C21/24, G01C21/26 take precedence
• CPC Class Codes: G01C 21/3461 Preferred or disfavoured areas, e.g. dangerous zones, toll or emission zones, intersections, manoeuvre types, segments such as motorways, toll roads, ferries
• CPC Class Codes: G06Q 10/109 Time management, e.g. calendars, reminders, meetings or time accounting
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 40/00 Finance; Insurance; Tax strategies; Processing of corporate or income taxes

Abstract

Described are methods and apparatuses, including computer program products, for tracking patterns associated with mobile devices. The system includes a server computing device configured to receive location information from a mobile device associated with a user. The location information includes location information based on GPS information sent from the mobile device. One or more activity patterns associated with the user of the mobile device are generated by the server computing device. The generating includes tracking the location information over a period of time and determining one or more categories of repeated activity based on the tracking.

Claims

1. A computerized method for generating and tracking activity patterns associated with mobile devices, the method comprising:

receiving, by a server computing device, location information from a mobile device associated with a user, the location information based on GPS information sent from the mobile device; and

tracking the location information over a period of time,

determining an occurrence of repeated activity based on the tracking; and

generating one or more activity patterns associated with the mobile device, wherein the one or more activity patterns are based on the occurrence of repeated activity

2. The method of claim 1, wherein tracking the location information comprises storing the location information in a storage device upon receiving the information from the mobile device.

3. The method of claim 1, wherein the one or more activity patterns include a travel route, a visited location, a purchase transaction, and a financial portfolio transaction.

4. The method of claim 1, the generating further comprising:

retrieving personal information associated with the user;

generating a characteristic of the one or more activity patterns based on the personal information; and

associating the characteristic with the one or more activity patterns.

5. The method of claim 4, wherein the personal information includes purchase history data, personal interests data, demographic data, social networking data, mobile device usage data, financial portfolio data, or any combination thereof.

6. The method of claim 1, further comprising comparing the one or more activity patterns with a second activity pattern of a second user to determine a match between the one or more activity patterns and the second activity pattern.

7. The method of claim 1, further comprising sending a message indicating the existence of a match between the one or more activity patterns of the user and an activity pattern of a second user.

8. The method of claim 7, wherein the message includes the location of the second user.

9. The method of claim 7, wherein the message is sent to a mobile device application, a web site, an email account, an instant messaging service, or any combination thereof.

10. The method of claim 7, wherein the message is generated based on receipt of a user query.

11. The method of claim 7, wherein the message comprises a graphical representation of the locations of the users in comparison to each other.

12. The method of claim 1, wherein the activity pattern comprises a travel route, further comprising determining a safety index based on crime data associated with locations in geographical proximity to the travel route.

13. The method of claim 12, wherein the crime data includes crime type, crime frequency, crime severity, crime density, or any combination thereof.

14. The method of claim 12, wherein the crime data is based on law enforcement reports, news reports, user-submitted reports, or any combination thereof.

15. The method of claim 12, further comprising displaying the safety index of one or more locations in proximity to the travel route.

16. The method of claim 12, further comprising providing an alternate route to the user, the alternate route having a higher safety index than the travel route.

17. The method of claim 1, wherein the activity pattern comprises a visited location, further comprising generating a purchase history based on transactions performed by the user at the visited location.

18. The method of claim 1, wherein the activity pattern comprises a purchase transaction, further comprising generating a message when the mobile device is in proximity to a location associated with the purchase transaction.

19. The method of claim 18, wherein the message comprises rebate information, discount information, product information, spending information, or any combination thereof.

20. The method of claim 1, wherein the activity pattern comprises a financial portfolio transaction, further comprising generating an alert for one or more securities associated with the financial portfolio transaction and sending the alert to the user.

21. The method of claim 1, wherein the one or more activity patterns are associated with the time of day at which the location information was received.

22. The method of claim 1, wherein receiving location information comprises automatically receiving location information at frequent intervals while the mobile device is active.

23. A system for tracking activity patterns associated with mobile devices, the system comprising:

a server computing device configured to;

receive location information from a mobile device associated with a user, the location information based on GPS information sent from the mobile device;

track the location information over a period of time;

determine an occurrence of repeated activity based on the tracking; and

generate one or more activity patterns associated with the mobile device, wherein the one or more activity patterns are based on the occurrence of repeated activity.

24. A system for tracking activity patterns associated with mobile devices, the system comprising:

means for receiving location information from a mobile device associated with a user, the location information based on GPS information sent from the mobile device; and

means for tracking the location information over a period of time;

means for determining an occurrence of repeated activity based on the tracking; and

means for generating one or more activity patterns associated with the mobile device, wherein the one or more activity patterns are based on the occurrence of repeated activity.

25. A computer program product for tracking activity patterns associated with mobile devices, tangibly embodied in a computer readable storage medium, the computer program product including instructions operable to cause a data processing apparatus to:

receive location information from a mobile device associated with a user, the location information based on GPS information sent from the mobile device; and

track the location information over a period of time;

determine an occurrence of repeated activity based on the tracking; and

generate one or more activity patterns associated with the mobile device, wherein the one or more activity patterns are based on the occurrence of repeated activity.