A geofence filtering method, system, and non-transitory computer readable medium, include a user location monitoring circuit configured to monitor a pinpoint location of a user and a boundary location of the user, a geofence determining circuit configured to determine a plurality of geofences that overlap with the boundary location of the user, the plurality of geofences being stored in a database, and a cognitive filtering and ranking circuit configured to filter the plurality of geofences that overlap with the boundary location of the user based on a cognitive factor and to rank the filtered geofences based on the cognitive factor to deliver to a user device when a pinpoint location of the user overlaps with the plurality of geofences.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A geofence filtering system comprising: a user location monitoring circuit configured to monitor a pinpoint location of a user and a boundary location of the user; a geofence determining circuit configured to determine a plurality of geofences that overlap with the boundary location of the user, the plurality of geofences being stored in a database; and a cognitive filtering and ranking circuit configured to filter the plurality of geofences that overlap with the boundary location of the user according to a behavioral measure of the user. 2. The system of claim 1, wherein the cognitive filtering and ranking circuit dynamically filters and ranks the plurality of geofences that overlap with the boundary location of the user such that the filtered and ranked geofences correspond to a real-time cognitive state when the pinpoint location of the user overlaps with the filtered and ranked geofences. 3. The system of claim 1, wherein the cognitive filtering and ranking circuit includes a learned mapping between a set of predetermined cognitive states and the plurality of geofences stored in the database, and wherein the cognitive filtering and ranking circuit continuously updates the ranking of the plurality of geofences based on the user having a predetermined cognitive state of the set of predetermined cognitive states. 4. The system of claim 1, wherein the cognitive filtering and ranking circuit filters all of the plurality of geofences based on the behavioral measure regardless of a location of the user. 5. The system of claim 1, wherein the cognitive filtering and ranking circuit stores at least one of the ranked geofences and the mappings in the database. 6. The system of claim 1, wherein the user selectively sets a size of the boundary location of the user. 7. The system of claim 1, wherein the cognitive filtering and ranking circuit selectively sets a size of the geofence. 8. The system of claim 1, wherein a number of the ranked filtered geofences delivered to the user device is based on an operating system of the user device. 9. The system of claim 1, wherein the behavioral measure includes at least one of: a dwell time of the user, a location history of the user; personal information of the user; weather data of the plurality of geofences; a time of day; a current state of traffic and traffic data between the plurality of geofences and the pinpoint location of the user; a social alert; a news alert; a number of people inside the plurality of geofences; an activity of the user device; biometric data of the user; a prior purchase behavior of the user, a speech analysis of the user; an analysis of user device usage; and venue information. 10. A geofence filtering method comprising: monitoring a pinpoint location of a user and a boundary location of the user; determining a plurality of geofences that overlap with the boundary location of the user, the plurality of geofences being stored in a database; and filtering the plurality of geofences that overlap with the boundary location of the user according to a behavioral measure of the user. 11. The method of claim 10, wherein the filtering and ranking further dynamically filters and ranks the plurality of geofences that overlap with the boundary location of the user such that the filtered and ranked geofences correspond to a real-time cognitive state when the pinpoint location of the user overlaps with the filtered and ranked geofences. 12. The method of claim 10, wherein the filtering and ranking further filters and ranks based on a learned mapping between a set of predetermined cognitive states and the plurality of geofences stored in the database, and wherein the filtering and ranking continuously updates the ranking of the plurality of geofences based on the user having a predetermined cognitive state of the set of predetermined cognitive states. 13. The method of claim 10, wherein the filtering and ranking further filters all of the plurality of geofences based on the behavioral measure regardless of a location of the user. 14. The method of claim 10, wherein the filtering and ranking further stores at least one of the ranked geofences and the mapping in the database. 15. The method of claim 10, wherein the user selectively sets a size of the boundary location of the user. 16. The method of claim 10, wherein the filtering and ranking selectively sets a size of the geofence. 17. A non-transitory computer-readable recording medium recording a geofence filtering program, the program causing a computer to perform: monitoring a pinpoint location of a user and a boundary location of the user; determining a plurality of geofences that overlap with the boundary location of the user, the plurality of geofences being stored in a database; and filtering the plurality of geofences that overlap with the boundary location of the user according to a behavioral measure of the user. 18. The non-transitory computer-readable recording medium of claim 17, wherein the filtering and ranking further dynamically filters and ranks the plurality of geofences that overlap with the boundary location of the user such that the filtered and ranked geofences correspond to a real-time cognitive state when the pinpoint location of the user overlaps with the filtered and ranked geofences. 19. The non-transitory computer-readable recording medium of claim 17, wherein the filtering and ranking further filters and ranks based on a learned mapping between a set of predetermined cognitive states and the plurality of geofences stored in the database, and wherein the filtering and ranking continuously updates the ranking of the plurality of geofences based on the user having one of the set of predetermined cognitive states. 20. The non-transitory computer-readable recording medium of claim 17, wherein the filtering and ranking further filters all of the plurality of geofences based on the behavioral measure regardless of a location of the user.