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