MOBILE DEVICE WITH PREDICTIVE ROUTING ENGINE

• US 20140279723A1
• Filed: 03/15/2013
• Published: 09/18/2014
• Est. Priority Date: 03/15/2013
• Status: Active Grant

• Current Assignee: Apple Inc.
• Original Assignee: Apple Inc.
• Inventors: McGavran, Christine B., Moore, Bradford A., Bolsinga, Gregory D., Dal Santo, Michael P., Marti, Lukas, Pylappan, Seejo K., van Os, Marcel
• Granted Patent: US 9,317,813 B2
• Time in Patent Office: Days
• US Class Current: 706/11
• CPC Class Codes: G01C 21/3617 using user history, behaviour, conditions or preferences, e.g. predicted or inferred from previous use or current movement
• CPC Class Codes: G01C 21/362 received from an external device or application, e.g. PDA, mobile phone or calendar application
• CPC Class Codes: G01C 21/3691 Retrieval, searching and output of information related to real-time traffic, weather, or environmental conditions arrangements for giving variable traffic instructions G08G1/09
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 5/02 Knowledge representation; Symbolic representation
• CPC Class Codes: G06N 5/022 Knowledge engineering; Knowledge acquisition
• CPC Class Codes: G06Q 10/109 Time management, e.g. calendars, reminders, meetings or time accounting
• CPC Class Codes: H04L 67/02 based on web technology, e.g. hypertext transfer protocol [HTTP]
• CPC Class Codes: H04L 67/10 in which an application is distributed across nodes in the network software deployment G06F8/60; multiprogramming arrangements G06F9/46
• CPC Class Codes: H04L 67/52 specially adapted for the location of the user terminal
• CPC Class Codes: H04L 67/535 Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34
• CPC Class Codes: H04W 4/025 using location based information parameters

Abstract

Some embodiments of the invention provide a mobile device with a novel route prediction engine that (1) can formulate predictions about current or future destinations and/or routes to such destinations for the device'"'"'s user, and (2) can relay information to the user about these predictions. In some embodiments, this engine includes a machine-learning engine that facilitates the formulation of predicted future destinations and/or future routes to destinations based on stored, user-specific data. The user-specific data is different in different embodiments. In some embodiments, the stored, user-specific data includes data about any combination of the following (1) previous destinations traveled to by the user, (2) previous routes taken by the user, (3) locations of calendared events in the user'"'"'s calendar, (4) locations of events for which the user has electronic tickets, and (5) addresses parsed from recent e-mails and/or messages sent to the user. The device'"'"'s prediction engine only relies on user-specific data stored on the device in some embodiments, relies only on user-specific data stored outside of the device by external devices/servers in other embodiments, and relies on user-specific data stored both by the device and by other devices/servers in other embodiments.

Claims

1. A mobile device comprising:

a location identification engine for identifying the location of the device;

a data storage for storing past locations of the device;

a prediction engine for predicting future destinations of the device.

2. The mobile device of claim 1, wherein the prediction engine is further for formulating routes to predicted destinations.

3. The mobile device of claim 1 further comprising a set of output engines for formulating and providing output data regarding predicted future destinations.

4. The mobile device of claim 1 further comprising a calendar and at least one electronic messaging program, wherein the data storage is further for storing data regarding locations of calendared events in the calendar, and addresses parsed from electronic messages received by the electronic messaging program.

5. The mobile device of claim 1, wherein the electronic messaging program is at least one of an email program or a text messaging program.

6. The mobile device of claim 1, wherein the past locations are destinations of past routes traversed by the device.

7. The mobile device of claim 6, wherein the past locations are locations along the past routes traversed by the device.

8. The mobile device of claim 1

further comprising a electronic ticket application,

wherein the data storage is further for storing data regarding a location of an event for which the electronic ticket application has a ticket.

9. The mobile device of claim 1 further comprising an interface for receiving addresses from a set of other devices associated with the device through a network, wherein the data storage is further for storing data regarding the received addresses.

10. The mobile device of claim 9, wherein the mobile device and the set of other devices are part of a group of devices that synchronize their content through a network-based synchronization system, wherein the received addresses are addresses extracted by at least one other device that is part of the group.

11. The mobile device of claim 1 further comprising a map application that generates a map display, receives data regarding a predicted destination from the prediction engine and displays the predicted destination on the map display.

12. The mobile device of claim 1 further comprising

a map application for generating a map display,

wherein the prediction engine is further for formulating routes to predicted destinations and providing the routes to the map application,

wherein the map application is further for displaying the predicted destination on the map display.

13. The mobile device of claim 12, wherein the prediction engine comprises a machine-learning engine for formulating predicted future destinations and future routes to the predicted future destinations.

14. A machine readable medium storing a program for providing information about potential destinations that a device may travel, the program for execution by at least one processing unit, the program comprising sets of instructions for:

identifying the location of the device;

storing past locations of the device;

predicting at least one future destination of the device based on the stored, past locations; and

providing an output based on the predicted destination.

15. The machine readable medium of claim 14, wherein the program further comprises a set of instructions for formulating a route to the predicted destination.

16. The machine readable medium of claim 14, wherein the program further comprises sets of instruction for:

extracting locations of calendared events stored by the device and extracting addresses contained in the electronic messages received by the device; and

using the extracted locations and addresses along with the stored past locations to predict the future destination.

17. The machine readable medium of claim 14, wherein the program further comprises sets of instructions for

receiving addresses from a set of other devices associated with the device through a network;

and

using the received addresses along with the extracted locations and addresses and the stored past locations to predict the future destination.

18. The machine readable medium of claim 14, wherein the past locations are locations along the past routes traversed by the device.

19. The machine readable medium of claim 14, wherein the past locations are past destinations of the device.

20. A machine-implemented method for providing information about potential destinations for a device to travel, the method comprising:

identifying the location of the device;

storing past locations of the device;

predicting at least one future destination of the device based on the stored, past locations; and

providing an output based on the predicted destination.