Abstract:
Techniques of range free proximity determination are described. A mobile device can determine an entry into or exit from a proximity fence upon determining that the mobile device is sufficiently close to a signal source. The proximity fence can be a virtual fence defined by the signal source and associated with a service. The mobile device can detect signals from multiple signal sources. The mobile device can determine that, among the signal sources, one or more signal sources are located closest to the mobile device based on a ranking of the signal sources using signal strength. The mobile device can determine a probability indicating a confident level of the ranking. The mobile device can determine that the mobile device entered or exited a proximity fence associated with a highest ranked signal source satisfying a confidence threshold.
Abstract:
Systems, methods and computer program products for providing location-based services triggered by a personal geofence are disclosed. A mobile device can determine that a venue located at a geographic location and frequently visited by the mobile device in the past is associated with a particular item, service, or activity. Upon receiving a query about the item, service, or activity, the mobile device can create a temporary geofence around the venue. Using past behavior patterns and a current location, the mobile device can determine a condition to trigger execution of an application program or display of certain content. The condition can be personalized to match a life style of a user of the mobile device. Accordingly, trigging the execution of the application program or the display of the content may be based on factors other than a distance between the mobile device and a point location.
Abstract:
Methods, program products, and systems for using a location fingerprint database to determine a location of a mobile device are described. A mobile device can use location fingerprint data received from a server to determine a location of the mobile device at the venue. The mobile device can obtain, from a sensor of the mobile device, a vector of sensor readings, each sensor reading can measure an environment variable, e.g., a signal received by the sensor from a signal source. The mobile device can perform a statistical match between the vector and the location fingerprint data. The mobile device can then estimate a current location of the mobile device based on the statistical match.
Abstract:
Techniques of range free proximity determination are described. A mobile device can determine an entry into or exit from a proximity fence upon determining that the mobile device is sufficiently close to a signal source. The proximity fence can be a virtual fence defined by the signal source and associated with a service. The mobile device can detect signals from multiple signal sources. The mobile device can determine that, among the signal sources, one or more signal sources are located closest to the mobile device based on a ranking of the signal sources using signal strength. The mobile device can determine a probability indicating a confident level of the ranking. The mobile device can determine that the mobile device entered or exited a proximity fence associated with a highest ranked signal source satisfying a confidence threshold.
Abstract:
Surveying techniques for generating location fingerprint data are described. A mobile device can survey a venue by measuring, at multiple locations at the venue, signals from one or more signal sources. At each location, the mobile device can take multiple measurements of signals. The mobile device can take each measurement at a distinct orientation. The measurements can be used to determine expected measurements of the signals at the venue. Differences between the multiple measurements of signals can be used to determine a variance of the expected measurements. The expected measurements and variance can be designated as location fingerprint data for the venue. The location fingerprint data can be used by mobile devices for determining a location at the venue.
Abstract:
Methods, program products, and systems for using a location fingerprint database to determine a location of a mobile device are described. A mobile device can use location fingerprint data and readings of a sensor to obtain a location observation. The mobile device can use the location observation in a particle filter for determining a location of the mobile device at a venue. Using state of movement of the mobile device and a map of the venue, the mobile device can determine one or more candidate locations of the device. The mobile device can then update the candidate locations using a next observation, and determine a probability density function based on the candidate locations. The mobile device can then present to a user a most probable location as a current location of the device in the venue.
Abstract:
Methods, program products, and systems for baseband location monitoring and related functions are disclosed. A mobile device can monitor its own current location using its baseband subsystem and decide whether to selectively activate its application subsystem based on whether particular conditions are satisfied by the current location. The mobile device can also correlate location and cellular signal information using its baseband subsystem and provide the correlated location and cellular signal information to a server. The server can receive the correlated location and cellular signal information from the baseband subsystems of a large number of widely distributed mobile devices and generate respective profiles of cellular network base stations that transmitted the cellular signals to the mobile devices. The profiles of the cellular network base stations can be used by the server in fulfilling subsequent positioning requests from mobile devices that do not currently have the baseband location monitoring enabled.