METHOD AND APPARATUS FOR INCREMENTALLY DETERMINING LOCATION CONTEXT

• US 20110070863A1
• Filed: 09/23/2009
• Published: 03/24/2011
• Est. Priority Date: 09/23/2009
• Status: Active Grant

• Current Assignee: WSOU Investments, LLC (WSOU Holdings, LLC)
• Original Assignee: Nokia Corporation
• Inventors: Ma, Yiming, Racz, David, Hankins, Rich
• Granted Patent: US 8,737,961 B2
• Time in Patent Office: Days
• US Class Current: 455/410
• CPC Class Codes: H04L 67/52 specially adapted for the location of the user terminal
• CPC Class Codes: H04M 1/72457 according to geographic location
• CPC Class Codes: H04W 12/08 Access security
• CPC Class Codes: H04W 4/02 Services making use of location information
• CPC Class Codes: H04W 4/021 Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences
• CPC Class Codes: H04W 4/027 using movement velocity, acceleration information
• CPC Class Codes: H04W 4/029 Location-based management or tracking services
• CPC Class Codes: H04W 4/50 Service provisioning or reconfiguring
• CPC Class Codes: H04W 48/04 based on user or terminal location or mobility data, e.g. moving direction, speed
• CPC Class Codes: H04W 64/00 Locating users or terminals or network equipment for network management purposes, e.g. mobility management

Abstract

Techniques to derive or predict location context for a user of a mobile device include receiving signal data that indicates a set of one or more distinct signal sources from which signals are received at the mobile device for each of multiple different times. The method further comprises determining whether the mobile device is moving outside a specified area at a current time based on the signal data. The method further comprises incrementing a count for a stationary state associated with the set of one or more distinct signal sources at the current time, if the mobile device is determined to be not moving outside the specified area. The method also comprises delivering a service to the mobile device based on the stationary state.

Claims

1. A method comprising:

causing at least in part a receiving of signal data that indicates a set of one or more distinct signal sources from which signals are received at a mobile device for each of a plurality of different times;

determining whether the mobile device is moving outside a specified area at a current time of the plurality of different times based on the signal data;

if the mobile device is determined to be not moving outside the specified area, then causing at least in part an incrementing of a count for a stationary state associated with the set of one or more distinct signal sources at the current time; and

causing at least in part initiation of delivery of a service to the mobile device based on the stationary state.

2. A method of claim 1, wherein determining whether the mobile device is moving outside the specified area comprises determining whether a measure of similarity, between a first set of one or more distinct signal sources in a time window ending at the current time and a second set of one or more distinct signal sources in a time window ending at a time earlier than the current time, is below a movement threshold.

3. A method of claim 1, wherein incrementing the count for the stationary state further comprises:

determining a conditional probability for each wireless transmitter of the set of wireless transmitters given an extant stationary state;

determining a conditional probability for the extant stationary state given the set of one or more distinct signal sources based on the conditional probability for each wireless transmitter of the set of wireless transmitters given the extant stationary state; and

updating a count of the extant stationary state if the conditional probability for the extant state given the set of one or more distinct signal sources is greater than a cluster threshold.

4. A method of claim 1, further comprising determining a primary set of stationary states, each stationary state in the primary set associated with a frequently incremented count for one or more similar sets of one or more distinct signal sources when the mobile device is not moving outside the specified area.

5. A method of claim 4, further comprising determining a transition state associated with a change from a first stationary state to a second stationary state of the primary set of stationary states.

6. A method of claim 5, wherein the first stationary state is identical to the second secondary state.

7. A method of claim 5, wherein determining the transition state further comprises incrementing a count for the transition state, wherein the count is associated with duration in the first stationary state and a timing context when the transition state is determined.

8. A method of claim 5, further comprising predicting the transition state based on a last stationary state before the current time and a time context for the current time and a history of occurrence of the transition state, wherein delivering the service to the mobile device based on the stationary state further comprises delivering the service based on the predicted transition state.

9. A method of claim 1, wherein delivering the service to the mobile device based on the stationary state further comprises determining a type of service based on communications by the user during the stationary state.

10. A method of claim 5, wherein delivering the service to the mobile device based on the stationary state further comprises determining a type of service based on a transition state that includes the stationary state.

11. A method of claim 5, further comprising predicting the transition state by:

determining a most probable transition state at the current time; and

determining a most probable transition state at a future time given the most probable transition state at the current time.

12. An apparatus comprising:

at least one processor; and

at least one memory including computer instructions, the at least one memory and computer instructions configured to, with the at least one processor, cause the apparatus at least to;

cause at least in part a receiving of signal data that indicates a set of one or more distinct signal sources from which signals are received at a mobile device for each of a plurality of different times;

determine whether the mobile device is moving outside a specified area at a current time of the plurality of different times based on the signal data;

if the mobile device is determined to be not moving outside the specified area, then incrementing a counter for a stationary state associated with the set of one or more distinct signal sources at the current time; and

cause at least in part initiation of delivery of a service to the mobile device based on the stationary state.

13. An apparatus of claim 12, wherein determining whether the mobile device is moving outside the specified area comprises determining whether a measure of similarity, between a first set of one or more distinct signal sources in a time window ending at the current time and a second set of one or more distinct signal sources in a time window ending at a time earlier than the current time, is below a movement threshold.

14. An apparatus of claim 12, wherein incrementing the count for the stationary state further comprises:

determining a conditional probability for each wireless transmitter of the set of wireless transmitters given an extant stationary state;

determining a conditional probability for the extant stationary state given the set of one or more distinct signal sources based on the conditional probability for each wireless transmitter of the set of wireless transmitters given the extant stationary state; and

updating a count of the extant stationary state if the conditional probability for the extant state given the set of one or more distinct signal sources is greater than a cluster threshold.

15. An apparatus of claim 12, the at least one memory and computer instructions further configured to, with the at least one processor, cause the apparatus at least to determine a primary set of stationary states, each stationary state in the primary set associated with a frequently incremented count for one or more similar sets of one or more distinct signal sources when the mobile device is not moving outside the specified area.

16. An apparatus of claim 15, the at least one memory and computer instructions further configured to, with the at least one processor, cause the apparatus at least to determine a transition state associated with a change from a first stationary state to a second stationary state of the primary set of stationary states.

17. An apparatus of claim 16, the at least one memory and computer instructions further configured to, with the at least one processor, cause the apparatus at least to predict the transition state by:

determining a most probable transition state at the current time; and

determining a most probable transition state at a future time given the most probable transition state at the current time.

18. A method comprising:

facilitating access to, including granting access rights for, a user interface configured to

receive signal data that indicates a set of one or more distinct signal sources from which signals are received at a mobile device for each of a plurality of different times, and

facilitating access to, including granting access rights for, a user interface that delivers a service to the mobile device based on a stationary state associated with a set of one or more distinct signal sources at a time when the mobile device is determined to be not moving outside a specified area based on the signal data.

19. A method of claim 18, wherein delivering a service based on the stationary state further comprising delivering the service based on a transition state associated with a change from a first stationary state to a second stationary state, each stationary state associated with one or more similar sets of one or more distinct signal sources when the mobile device is not moving outside the specified area.

20. A method of claim 18, wherein the transition state is predicted based on a last stationary state before the current time and a time context for the current time and a history of occurrence of the transition state.