GEOFENCES FROM CONTEXT AND CROWD-SOURCING
First Claim
1. A system, comprising:
- an access component that accesses user context data of a user and ambient conditions data as related to a geographical location;
a data analysis component that analyzes at least one of the user context data or the ambient conditions data to generate geofence properties that relate in part to size, placement, and shape of a geofence;
a geofence component that automatically generates the geofence for the geographical location based on the geofence properties, and manages changes to the geofence based on changes to the geofence properties; and
at least one microprocessor that executes computer-executable instructions associated with each of the access component, the data analysis component, and the geofence component.
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Accused Products
Abstract
Architecture that enables the capability to more effectively define and resize geofences to provide improved geofence utility based on rich context and crowd-sourced data. The architecture enables the intelligent placement of geofences based on rich context that includes both user context and ambient context such as the (predicted or implicitly/explicitly defined) user'"'"'s travel path, mode of transport, the type of the entity to be visited by the user and geofenced, and the user incentive for visiting the entity to be geofenced. The ambient context includes non-user specific information such as external conditions that may limit or thwart user mobility such as traffic and weather conditions. The rich context and crowd-sourced data assist in improving the spatiotemporal accuracy of suggested/constructed geofences thereby creating a “shaped” geofence that is sufficiently defined to approximate the shape of the entity being geofenced with some degree of accuracy.
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Citations
20 Claims
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1. A system, comprising:
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an access component that accesses user context data of a user and ambient conditions data as related to a geographical location; a data analysis component that analyzes at least one of the user context data or the ambient conditions data to generate geofence properties that relate in part to size, placement, and shape of a geofence; a geofence component that automatically generates the geofence for the geographical location based on the geofence properties, and manages changes to the geofence based on changes to the geofence properties; and at least one microprocessor that executes computer-executable instructions associated with each of the access component, the data analysis component, and the geofence component. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A method, comprising acts of:
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accessing user context data of a user that relates to a type of entity as a destination; accessing ambient context data that relates to external conditions which influence travel to the entity; automatically generating a geofence based on the user context data and ambient context data; computing a size of the geofence based on the type of the entity and the external conditions which influence travel to the entity; and placing the geofence relative to the entity. - View Dependent Claims (10, 11, 12, 13, 14, 15)
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16. A computer-readable storage medium comprising computer-executable instructions that when executed by a microprocessor, cause the microprocessor to perform acts of:
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accessing crowd-sourced context data that relates to a type of geographical location; creating a virtual perimeter of the geographical location based on the crowd-sourced data, the virtual perimeter shaped to the geographical location; automatically generating a geofence for the geographical location according to the shaped virtual perimeter and aligning the geofence to match outline of the geographical location; and sizing the geofence based on user context data and ambient conditions data that influence travel to the geographical location. - View Dependent Claims (17, 18, 19, 20)
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Specification