IDENTIFYING GEOSPATIAL PATTERNS FROM DEVICE DATA

• US 20140040179A1
• Filed: 08/05/2013
• Published: 02/06/2014
• Est. Priority Date: 12/02/2009
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Herzog, Shai, Lin, Jyh-Han, Abel, Miller Thomas, Khosravy, Moe, Weber, Karon A., Lau, James Kai Yu, Morris, Katrika
• Granted Patent: US 9,536,202 B2
• Time in Patent Office: Days
• US Class Current: 706/52
• CPC Class Codes: G06N 5/048 Fuzzy inferencing
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G09B 29/007 using computer methods

Abstract

Determining geospatial patterns from device data collected from a plurality of computing devices. The devices represent, for example, a plurality of sources providing the device data. The device data describes the computing devices and/or environments thereof. Some embodiments present the determined patterns to users for editing, update maps with the edited patterns, and distribute the maps to the users. The maps are stored to create a searchable map library.

Claims

1. A system for creating temporal maps based on geospatial patterns, said system comprising:

a memory area for storing device data received from one or more of a plurality of mobile computing devices, said device data describing said one or more of the plurality of mobile computing devices or environments thereof; and

a processor programmed to;

infer at least one temporal geospatial pattern from the received device data;

generate a temporal map based at least on the inferred temporal geospatial pattern;

compare the temporal map to a previously generated temporal map sent to the one or more of the plurality of mobile computing devices;

select, based on the comparison, at least one of the one or more of the plurality of mobile computing devices that were sent the previously generated temporal map; and

provide the generated temporal map to the selected at least one of the one or more of the plurality of mobile computing devices.

2. The system of claim 1, wherein the processor is further programmed to generate a confidence factor associated with the inferred temporal geospatial pattern, the confidence factor being accompanied by a question for providing missing information or correcting the inferred temporal geospatial pattern.

3. The system of claim 2, wherein the confidence factor includes a weight value based on one or more of the following:

a quantity of the mobile computing devices associated with the inferred temporal geospatial pattern, the received device data, and a location of the one or more of the plurality of mobile computing devices.

4. The system of claim 1, wherein the device data describes one or more of the following:

location, elevation, heading, speed, acceleration, direction, weather, messages, user interaction, image data, voice data, text data, and files.

5. The system of claim 1, wherein the temporal geospatial pattern includes one or more of the following:

a navigation path, a point of interest, one or more time periods, a weight value, a dwell time at a location, and a social event.

6. The system of claim 1, wherein a level of relevance associated with the inferred temporal geospatial pattern is determined from one or more of the following:

a defined user preference, user behavior history, and a location of a user.

7. The system of claim 1, wherein the processor is further programmed to provide a context of the inferred temporal geospatial pattern based on public event data or user data of a user associated with one of the plurality of mobile computing devices.

8. A method comprising:

accessing, by a processor, device data received from a first plurality of computing devices;

identifying at least one geospatial pattern from the accessed device data;

defining map data using the identified at least one geospatial pattern;

determining whether the identified at least one geospatial pattern is related to a previously identified pattern;

selecting a second plurality of computing devices for receiving the defined map data based on the determination, the second plurality of computing devices corresponding to a third plurality of computing devices previously selected to receive the previously identified pattern.

9. The method of claim 8, wherein accessing the device data comprises accessing device data received within a pre-defined time period.

10. The method of claim 8, further comprising:

identifying users associated with the first plurality of computing devices; and

obtaining user data associated with the identified users, wherein identifying the at least one geospatial pattern comprises correlating the accessed device data with the obtained user data.

11. The method of claim 10, wherein obtaining the user data comprises obtaining one or more of the following:

calendar data, message data, task data, social networking data, location data, and a purchase history.

12. The method of claim 8, wherein the defined map data indicates a hazard at a location, and further comprising selecting the second plurality of computing devices based on the location.

13. The method of claim 8, further comprising:

identifying another geospatial pattern relating to said at least one geospatial pattern; and

notifying the first plurality of computing devices of the identified another geospatial pattern.

14. The method of claim 8, wherein defining the map data comprises defining recommendations based on the identified at least one geospatial pattern.

15. The method of claim 8, wherein the second plurality of computing devices includes one or more of the first plurality of computing devices.

16. One or more computer storage media storing computer-executable components, said components comprising:

an interface component that when executed by at least one processor causes the at least one processor to receive device data from one or more of a plurality of computing devices, said device data describing said one or more of the plurality of computing devices or environments thereof;

a synthesis component that when executed by at least one processor causes the at least one processor to identify at least one geospatial pattern from the device data received by the interface component; and

a group component that when executed by at least one processor causes the at least one processor to propagate the at least one geospatial pattern identified by the synthesis component to at least one of the one or more of the plurality of computing devices which contributed the device data for identification of the at least one geospatial pattern.

17. The computer storage media of claim 16, further comprising a map component that when executed by at least one processor causes the at least one processor to generate a map based on the at least one geospatial pattern identified by the synthesis component.

18. The computer storage media of claim 16, further comprising a feedback component that when executed by at least one processor causes the at least one processor to identify at least one user for editing, confirming or rejecting the at least one geospatial pattern.

19. The computer storage media of claim 16, wherein the at least one geospatial pattern is selected for propagation based on responses received from a threshold quantity of the one or more of the plurality of computing devices.

20. The computer storage media of claim 16, wherein a reason for the identified at least one geospatial pattern is inferred based on the device data received from a threshold quantity of the one or more of the plurality of computing devices.