Microsoft Technology Licensing, LLC

Mark A Inderhees

Sanjib Saha

Janet Lynn Schneider

Frank Gorgenyi

Fernando Gonzalez

Stuart J Harper

Shaun C Hedrick

Parmjeet Singh

Ashish Vijay Gadre

Cristina Del Amo Casado

Lanny D Natucci, Jr

Dino Natucci

Robert Dufalo

Janet L Schneider

Jr Natucci Lanny D

Lanny D Natucci Jr

The location of a computing device is determined, and the location of an area of interest that is a geographic area referred to as a geo-fence is identified. The accuracy of the determined location of the computing device has an associated uncertainty, so the exact position of the computing device cannot typically be pinpointed. In light of this, the uncertainty associated with the determined location is evaluated relative to the size of the geo-fence in order to determine whether the computing device is inside the geo-fence or outside the geo-fence. Based on this determination, various actions can be taken if the user is entering the geo-fence, exiting the geo-fence, remaining in the geo-fence for at least a threshold amount of time, and so forth.

Detecting geo-fence events using varying confidence levels

A computing device includes at least one processor and a memory, the memory storing computer-executable instructions for causing the device to be configured to load a subset of geo-fences from secondary storage to primary storage for tracking by the computing device, the subset of geo-fences selected from a set of available geo-fences stored in the secondary storage, based on a selection criteria. The computing device further creates a boundary geo-fence with a radius corresponding to a distance between a current location of the computing device and an edge of a geo-fence in the subset of geo-fences that is furthest from the current location of the computing device. Upon detecting a geo-fence event associated with a new location of the computing device in relation to the boundary geo-fence, a new subset of geo-fences is re-loaded, and a new boundary geo-fence is created based on the new location of the computing device.

Scalability and reliability of hardware geo-fencing with failover support

One disclosed example provides a method including compiling and storing on the computing device a list of positioning signals each associated with a geographic location, detecting one or more currently available positioning signals, comparing the one or more currently available positioning signals to the list of positioning signals, and if one or more currently available positioning signals matches one or more matching positioning signals stored in the list, then determining the current geographic location based upon the one or more matching stored positioning signals.

Cache-based location determination

Systems and methods disclosed herein may include tracking one or more geo-fences using a GNSS hardware processor within a computing device. The tracking may use at least one GNSS signal. State changes of the one or more geo-fences during the tracking may be saved in a shared state database. The shared state database may be shared between the GNSS hardware processor and an application processor within the computing device. Upon detecting a deterioration of the at least one GNSS signal, tracking the one or more geo-fences may be switched from using the GNSS hardware processor to using the application processor. After the switching, an initial state of each of the one or more geo-fences may be set by using states currently stored in the shared state database prior to the switching.

Improving scalability and reliability of hardware geo-fencing with failover support

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Woodinville, WA, United States of America

Mark A Inderhees