DETERMINING A DYNAMIC USER PROFILE INDICATIVE OF A USER BEHAVIOR CONTEXT WITH A MOBILE DEVICE

• US 20120185419A1
• Filed: 10/07/2011
• Published: 07/19/2012
• Est. Priority Date: 01/13/2011
• Status: Active Grant

• Current Assignee: Qualcomm, Inc.
• Original Assignee: Qualcomm, Inc.
• Inventors: KUHN, Lukas Daniel, NANDA, Sanjiv, NARAYANAN, Vidya
• Granted Patent: US 8,719,188 B2
• Time in Patent Office: Days
• US Class Current: 706/12
• CPC Class Codes: G06N 5/048 Fuzzy inferencing
• CPC Class Codes: H04M 1/72454 according to context-related or environment-related conditions
• CPC Class Codes: H04M 2242/30 Determination of the location of a subscriber
• CPC Class Codes: H04M 3/42136 Administration or customisation of services

Abstract

Methods, apparatuses and articles of manufacture for use in a mobile device to determine whether a dynamic user profile is to transition from a first state to a second state based, at least in part, on one or more sensed indicators. The dynamic user profile may be indicative of one or more current inferable user behavior contexts for a user co-located with the mobile device. The mobile device may transition a dynamic user profile from a first state to a second state, in response to a determination that the dynamic user profile is to transition from the first state to the second state, and operatively affect one or more functions performed, at least in part, by the mobile device based, at least in part, on the transition of the dynamic user profile to the second state.

Claims

1. A method comprising, at a mobile device:

determining whether a dynamic user profile is to transition from a first state to a second state based, at least in part, on one or more sensed indicators, said dynamic user profile being indicative of a current inferable user behavior context for a user co-located with said mobile device;

transitioning said dynamic user profile from said first state to said second state in response to a determination that said dynamic user profile is to transition from said first state to said second state; and

operatively affecting one or more functions performed, at least in part, by said mobile device based, at least in part, on said transition of said dynamic user profile from said first state to said second state.

2. The method as recited in claim 1, wherein determining whether said dynamic user profile is to transition from said first state to said second state further comprises:

determining whether said one or more sensed indicators matches one or more stored patterns or models of behavior previously associated with at least said first state; and

in response to a determination that said one or more sensed indicators does not match said one or more stored patterns or models of behavior previously associated with at least said first state, determining that said dynamic user profile is to transition from said first state to said second state.

3. The method as recited in claim 2, wherein said second state comprises a previously unknown state, the method further comprising:

establishing and storing one or more new patterns or models of behavior associated with said previously unknown state based, at least in part, on said one or more sensed indicators.

4. The method as recited in claim 3, wherein establishing said one or more new patterns or models of behavior associated with said previously unknown state further comprises:

identifying said current inferable user behavior context for said user with regard to said second state.

5. The method as recited in claim 1, wherein said second state comprises a previously known state and wherein determining whether said dynamic user profile is to transition from said first state to said second state further comprises:

determining whether said one or more sensed indicators matches one or more stored patterns or models of behavior previously associated with at least said second state; and

in response to a determination that said one or more sensed indicators does match said one or more stored patterns or models of behavior previously associated with at least said second state, determining that said dynamic user profile is to transition from said first state to said second state.

6. The method as recited in claim 1, wherein said current inferable user behavior context is based, at least in part, on one or more points of interest.

7. The method as recited in claim 1, wherein said current inferable user behavior context is based, at least in part, on one or more user activities.

8. The method as recited in claim 1, wherein said current inferable user behavior context is based, at least in part, on one or more time periods.

9. The method as recited in claim 1, wherein at least one of said one or more sensed indicators is based, at least in part, on one or more wireless signals received from one or more other devices via one or more network interfaces of said mobile device.

10. The method as recited in claim 1, wherein at least one of said one or more sensed indicators is based, at least in part, on either or both of:

one or more sensed inertial movements of said mobile device from one or more inertial sensors of said mobile device, or one or more sensed environmental measurements from one or more environmental sensors.

11. The method as recited in claim 1, wherein at least one of said one or more sensed indicators is based, at least in part, on either or both of:

one or more encoded audio signals recorded using a microphone of said mobile device, or one or more encoded images recorded using a light sensitive environmental sensor of said mobile device.

12. The method as recited in claim 1, wherein at least one of said one or more sensed indicators is based, at least in part, on a current estimated position location of said mobile device.

13. The method as recited in claim 1, wherein at least one of said one or more sensed indicators is based, at least in part, on either or both of:

an estimated future destination of said mobile device, or an estimated route of travel of said mobile device.

14. The method as recited in claim 1, wherein at least one of said one or more sensed indicators is based, at least in part, on either or both of:

one or more user schedule files accessible via said mobile device, or one or more user communication files accessible via said mobile device.

15. The method as recited in claim 1, wherein said one or more functions performed, at least in part, by said mobile device comprises at least one of:

one or more location based service functions, one or more position location functions, one or more navigation functions, one or more network communication functions, or one or more user output functions.

16. An apparatus for use in a mobile device, the apparatus comprising:

means for determining whether a dynamic user profile is to transition from a first state to a second state based, at least in part, on one or more sensed indicators, said dynamic user profile being indicative of a current inferable user behavior context for a user co-located with said mobile device;

means for transitioning said dynamic user profile from said first state to said second state, in response to a determination that said dynamic user profile is to transition from said first state to said second state; and

means for operatively affecting one or more functions performed, at least in part, by said mobile device based, at least in part, on said transition of said dynamic user profile from said first state to said second state.

17. The apparatus as recited in claim 16, further comprising:

means for storing one or more patterns or models of behavior previously associated with at least said first state;

means for determining whether said one or more sensed indicators matches said one or more stored patterns or models of behavior previously associated with at least said first state; and

means for determining that said dynamic user profile is to transition from said first state to said second state, in response to a determination that said one or more sensed indicators does not match said one or more stored patterns or models of behavior previously associated with at least said first state.

18. The apparatus as recited in claim 17, wherein said second state comprises a previously unknown state and further comprising:

means for establishing one or more new patterns or models of behavior associated with said previously unknown state based, at least in part, on said one or more sensed indicators.

19. The apparatus as recited in claim 18, further comprising:

means for identifying said current inferable user behavior context for said user with regard to said second state.

20. The apparatus as recited in claim 16, wherein said second state comprises a previously known state, the apparatus further comprising:

means for determining whether said one or more sensed indicators matches one or more stored patterns or models of behavior previously associated with at least said second state; and

means for determining that said dynamic user profile is to transition from said first state to said second state, in response to a determination that said one or more sensed indicators does match said one or more stored patterns or models of behavior previously associated with at least said second state.

21. The apparatus as recited in claim 16, wherein said current inferable user behavior context is based, at least in part, on one or more points of interest.

22. The apparatus as recited in claim 16, wherein said current inferable user behavior context is based, at least in part, on one or more user activities.

23. The apparatus as recited in claim 16, wherein said current inferable user behavior context is based, at least in part, on one or more time periods.

24. The apparatus as recited in claim 16, further comprising:

means for receiving one or more wireless signals from one or more other devices; and

wherein at least one of said one or more sensed indicators is based, at least in part, on at least one received wireless signal.

25. The apparatus as recited in claim 16, further comprising:

means for sensing one or more inertial movements of said mobile device; and

wherein at least one of said one or more sensed indicators is based, at least in part, on at least one sensed inertial movement of said mobile device.

26. The apparatus as recited in claim 16, further comprising:

means for obtaining one or more environmental measurements; and

wherein at least one of said one or more sensed indicators is based, at least in part, on at least one obtained environmental measurement.

27. The apparatus as recited in claim 16, further comprising:

means for obtaining a current estimated position location of said mobile device; and

wherein at least one of said one or more sensed indicators is based, at least in part, on said current estimated position location.

28. The apparatus as recited in claim 16, further comprising:

means for accessing either or both of;

one or more user schedule files, or one or more user communication files; and

wherein at least one of said one or more sensed indicators is based, at least in part, on either or both of;

at least one of said user schedule files, or at least one of said user communication files.

29. The apparatus as recited in claim 16, wherein said one or more functions performed, at least in part, by said mobile device comprises at least one of:

one or more location based service functions, one or more position location functions;

one or more navigation functions, one or more network communication functions, or one or more user output functions.

30. A mobile device comprising:

memory; and

a processing unit to;

determine whether a dynamic user profile is to transition from a first state to a second state based, at least in part, on one or more sensed indicators in said memory, said dynamic user profile being indicative of a current inferable user behavior context for a user co-located with said mobile device;

transition said dynamic user profile from said first state to said second state, in response to a determination that said dynamic user profile is to transition from said first state to said second state; and

operatively affect one or more functions performed, at least in part, by said mobile device based, at least in part, on said transition of said dynamic user profile from said first state to said second state.

31. The mobile device as recited in claim 30, said processing unit to further:

determine whether said one or more sensed indicators matches one or more patterns or models of behavior stored in said memory and previously associated with at least said first state; and

in response to a determination that said one or more sensed indicators does not match said one or more stored patterns or models of behavior previously associated with at least said first state, determine that said dynamic user profile is to transition from said first state to said second state.

32. The mobile device as recited in claim 31, wherein said second state comprises a previously unknown state and said processing unit to further:

establish one or more new patterns or models of behavior associated with said previously unknown state based, at least in part, on said one or more sensed indicators; and

indicate said one or more new patterns or models of behavior associated with said previously unknown state to said memory for storage therein.

33. The mobile device as recited in claim 32, said processing unit to further:

identify said current inferable user behavior context for said user with regard to said second state.

34. The mobile device as recited in claim 30, wherein said second state comprises a previously known state and said processing unit to further:

determine whether said one or more sensed indicators matches one or more patterns or models of behavior stored in said memory and previously associated with at least said second state; and

in response to a determination that said one or more sensed indicators does match said one or more stored patterns or models of behavior previously associated with at least said second state, determine that said dynamic user profile is to transition from said first state to said second state.

35. The mobile device as recited in claim 30, wherein said current inferable user behavior context is based, at least in part, on one or more points of interest.

36. The mobile device as recited in claim 30, wherein said current inferable user behavior context is based, at least in part, on one or more user activities.

37. The mobile device as recited in claim 30, wherein said current inferable user behavior context is based, at least in part, on one or more time periods.

38. The mobile device as recited in claim 30, further comprising:

a network interface; and

wherein at least one of said one or more sensed indicators is based, at least in part, on one or more wireless signals received from one or more other devices via said network interface.

39. The mobile device as recited in claim 30, further comprising:

one or more inertial sensors; and

wherein at least one of said one or more sensed indicators is based, at least in part, on one or more sensed inertial movements of said mobile device from said one or more inertial sensors.

40. The mobile device as recited in claim 30, further comprising:

one or more environmental sensors; and

wherein at least one of said one or more sensed indicators is based, at least in part, on one or more sensed environmental measurements from said one or more environmental sensors.

41. The mobile device as recited in claim 30, further comprising:

a location receiver to estimate a current estimated position location of said mobile device; and

wherein at least one of said one or more sensed indicators is based, at least in part, on said current estimated position location of said mobile device.

42. The mobile device as recited in claim 30, said processing unit to further:

determine either or both of an estimated future destination of said mobile device or an estimated route of travel of said mobile device; and

wherein at least one of said one or more sensed indicators is based, at least in part, on either or both of;

said estimated future destination of said mobile device, or said estimated route of travel of said mobile device.

43. The mobile device as recited in claim 30, wherein at least one of said one or more sensed indicators is based, at least in part, on either or both of:

one or more user schedule files accessible via said memory, or one or more user communication files accessible via said memory.

44. The mobile device as recited in claim 30, wherein said one or more functions performed, at least in part, by said mobile device comprises at least one of:

one or more location based service functions, one or more position location functions, one or more navigation functions, one or more network communication functions, or one or more user output functions.

45. An article comprising:

a non-transitory computer-readable medium having stored therein computer-readable instructions executable by one or more processing units in a mobile device to;

determine whether a dynamic user profile is to transition from a first state to a second state based, at least in part, on one or more sensed indicators, said dynamic user profile being indicative of a current inferable user behavior context for a user co-located with said mobile device;

transition said dynamic user profile from said first state to said second state, in response to a determination that said dynamic user profile is to transition from said first state to said second state; and

operatively affect one or more functions performed, at least in part, by said mobile device based, at least in part, on said transition of said dynamic user profile from said first state to said second state.

46. The article as recited in claim 45, said computer-readable instructions being further executable by said one or more processing units to:

determine whether said one or more sensed indicators matches one or more stored patterns or models of behavior previously associated with at least said first state; and

determine that said dynamic user profile is to transition from said first state to said second state, in response to a determination that said one or more sensed indicators does not match said one or more stored patterns or models of behavior previously associated with at least said first state.

47. The article as recited in claim 46, wherein said second state comprises a previously unknown state;

and

said computer-readable instructions being further executable by said one or more processing units to establish one or more new patterns or models of behavior associated with said previously unknown state based, at least in part, on said one or more sensed indicators.

48. The article as recited in claim 47, said computer-readable instructions being further executable by said one or more processing units to identify said current inferable user behavior context for said user with regard to said second state.

49. The article as recited in claim 45, wherein said second state comprises a previously known state;

and

said computer-readable instructions being further executable by said one or more processing units to;

determine whether said one or more sensed indicators matches one or more stored patterns or models of behavior previously associated with at least said second state; and

determine that said dynamic user profile is to transition from said first state to said second state, in response to a determination that said one or more sensed indicators does match said one or more stored patterns or models of behavior previously associated with at least said second state.

50. The article as recited in claim 45, wherein said current inferable user behavior context is based, at least in part, on one or more points of interest.

51. The article as recited in claim 45, wherein said current inferable user behavior context is based, at least in part, on one or more user activities.

52. The article as recited in claim 45, wherein said current inferable user behavior context is based, at least in part, on one or more time periods.

53. The article as recited in claim 45, wherein at least one of said one or more sensed indicators is based, at least in part, on at least one received wireless signal.

54. The article as recited in claim 45, wherein at least one of said one or more sensed indicators is based, at least in part, on at least one sensed inertial movement of said mobile device.

55. The article as recited in claim 45, wherein at least one of said one or more sensed indicators is based, at least in part, on at least one sensed environmental measurement.

56. The article as recited in claim 45, wherein at least one of said one or more sensed indicators is based, at least in part, on a current estimated position location.

57. The article as recited in claim 45, wherein at least one of said one or more sensed indicators is based, at least in part, on one or both of:

one or more user schedule files, or one or more user communication files.

58. The article as recited in claim 45, wherein said one or more functions performed, at least in part, by said mobile device comprises at least one of:

one or more location based service functions, one or more position location functions, one or more navigation functions, one or more network communication functions, or one or more user output functions.