Automated determination of mobile user locations and deduction of user activities at the user locations

• US 10,051,433 B2
• Filed: 08/16/2016
• Issued: 08/14/2018
• Est. Priority Date: 10/10/2013
• Status: Active Grant

• Current Assignee: Aura Home, Inc. (Pushd, Inc.)
• Original Assignee: Pushd, Inc.
• Inventors: Cherry, Ben, Chowdhury, Abdur, Frieder, Ophir, Jensen, Eric, Sanford, Matt
• Primary Examiner(s): Keller, Michael A
• Application Number:
  US15/237,791
• Publication Number:
  US 20160360379A1
• Time in Patent Office: 728 Days
• CPC Class Codes: H04L 51/52 for supporting social networking services
• CPC Class Codes: H04L 67/12 specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
• CPC Class Codes: H04L 67/53 using third party service providers
• 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 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 4/027 using movement velocity, acceleration information
• CPC Class Codes: H04W 4/029 Location-based management or tracking services
• CPC Class Codes: H04W 4/21 for social networking applications
• CPC Class Codes: H04W 4/30 Services specially adapted for particular environments, situations or purposes
• CPC Class Codes: H04W 52/0229 where the received signal is a wanted signal
• CPC Class Codes: Y02D 30/70 in wireless communication networks

Abstract

A method, system, and/or apparatus for automatically tracking a mobile user using the user'"'"'s mobile device. This invention is particularly useful in the field of social media, such as for detecting and tracking the location and activity of a user and her community. The method or implementing software application uses or relies upon location information available on the mobile device from any source, such as cell phone usage and/or other device applications. The social media system automatically determines a location type and/or user activity from context information. The context information can include current and past location and user and/or community information, time-dependent information, and third party information. The location activities can be presented to the community using pictograms selected to represent user activities.

Claims

1. A method of determining locations and/or activities of a user participating in a social networking service, the method executed by a computer system and comprising:

automatically determining a positional destination of a user, wherein automatically determining a positional destination of a user comprises;

providing a location module on a mobile device configured to receive location transmissions;

placing the location module into a sleep mode;

awakening the location module upon receipt of a first location transmission; and

determining a first location with the location module

incrementing a timer count configured to monitor a duration of time, wherein whenever a time exceeds a predetermined time allocation, the location module is placed into the sleep mode;

incrementing a stationary counter configured to monitor a duration of time since a previous detected movement of the mobile user;

receiving a second location transmission of a second location;

comparing the second location to the first location;

calculating a rate of travel when the second location differs from the first location, wherein if the rate of travel exceeds a predetermined threshold the location module is placed into the sleep mode;

receiving a third location transmission of a third location;

comparing the third location to at least one of the first location or the second location;

further incrementing the stationary counter when the second or third location is the same as the first location;

determining an arrival event upon reaching a predetermined arrival threshold of the stationary counter;

storing data of all locations; and

placing the location module into the sleep mode;

automatically determining context information about the positional destination without input by the user;

automatically deducing as user information a location type and/or user activity of the positional destination from the context information; and

automatically sharing the user information in the social networking service.

2. The method of claim 1, wherein the deducing as user information comprises searching third party information about the locations.

3. The method of claim 1, further comprising automatically storing past location type and/or user activity of each of the locations, wherein the user information is automatically deduced as a function of the stored past location type and/or user activity of the each of the locations.

4. The method of claim 3, wherein the past location type and/or user activity of at least one the locations is from a second user.

5. The method of claim 3, wherein the past location type and/or user activity of at least one the locations is from each of a plurality of social media community members of the user.

6. The method of claim 3, further comprising reducing possible location types and/or user activities as a function of the past location type and/or user activity of the locations.

7. The method of claim 3, further comprising ranking the past location type and/or user activity of the locations for deducing the user information.

8. The method of claim 3, automatically comparing the context information of the locations with past context information of the past location type and/or user activity of the locations.

9. The method of claim 8, wherein the past context information comprises the past location type and/or user activity of the locations from each of a plurality of social media community members of the user.

10. The method of claim 8, wherein the context information comprises time of day.

11. The method of claim 10, further comprising ranking possible location type and/or user activity of the locations during a time period corresponding to the time of day.

12. The method of claim 8, wherein the context information comprises presence of any community members.

13. The method of claim 1, further comprising automatically determining the user has arrived at the destination.

14. The method of claim 1, wherein the context information comprises time-dependent information, community information, and/or third-party information about the positional destination.

15. The method of claim 1, further comprising comparing past context information for past visits to the positional destination, by the user and/or community members of the user, to a current context of the positional destination to deduce the user information.

16. The method of claim 1, further comprising reducing possible location types and/or user activities as a function of the past location type and/or user activity of the positional destination for a given time period.

17. The method of claim 1, wherein deducing as user information comprises:

automatically associating the user with a second user at the positional destination, wherein a second user location and/or second user activity is determined; and

automatically inferring the location type and/or user activity from the second user location and/or activity.

18. The method of claim 17, further comprising automatically asking the user for confirmation of the location type and/or user activity based upon the associated second user location and/or second user activity before sharing.