MOBILE DEVICE WITH PREDICTIVE ROUTING ENGINE

• US 20160212229A1
• Filed: 03/30/2016
• Published: 07/21/2016
• 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 10,579,939 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• 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

1-20. -20. (canceled)

21. A non-transitory machine readable medium storing a program for providing information about potential destinations for a first device, the program for execution by at least one processing unit, the program comprising sets of instructions for:

receiving an address from a second device;

receiving instructions to open a map application on the first device; and

presenting the received address as a potential destination for the first device.

22. The non-transitory machine readable medium of claim 21, wherein the set of instructions for presenting the received address comprises a set of instructions for presenting the received address in a search display area of the map application, the search display area for displaying prior location searches that the map application has performed on the first device.

23. The non-transitory machine readable medium of claim 21, wherein the first and second devices are devices associated with a particular user.

24. The non-transitory machine readable medium of claim 23, wherein the first and second devices communicate with a server, the server for providing cloud synchronization services for the first and second devices.

25. The non-transitory machine readable medium of claim 21, wherein the received address is an address associated with a recent task performed on the second device.

26. The non-transitory machine readable medium of claim 25, wherein the recent task is one of a search in a web browser and a communication with a contact.

27. The non-transitory machine readable medium of claim 21, wherein the program further comprises sets of instructions for:

identifying a location of the first device;

storing past locations of the first device and the received address from the second device; and

predicting at least one future destination of the first device based on a current location of the first device and the stored, past locations and the received address from the second device, wherein presenting the received address as a potential destination for the first device is based on the prediction of the received address as a future destination of the first device.

28. The non-transitory machine readable medium of claim 27, wherein the set of instructions for predicting at least one future destination comprises a set of instructions for calculating a probability of the at least one future destination being an actual destination, wherein the set of instructions for presenting the received address comprises a set of instructions for presenting the predicted destinations ordered according to the calculated probability.

29. The non-transitory machine readable medium of claim 28, wherein the set of instructions for predicting at least one future destination comprises a set of instructions for updating the calculated probability, wherein the set of instructions for presenting the received address comprises a set of instructions for updating the presentation based on the updated calculated probability.

30. A first mobile device comprising:

a set of processing units; and

a non-transitory machine readable medium storing a program which when executed by at least one processing unit, provides information about potential destinations for the first mobile device, the program comprising sets of instructions for;

receiving an address from a second device;

receiving instructions to open a map application on the first mobile device; and

presenting the received address as a potential destination for the first mobile device.

31. The first mobile device of claim 30, wherein the set of instructions for presenting the received address comprises a set of instructions for presenting the received address in a search display area of the map application, the search display area for displaying prior location searches that the map application has performed on the first mobile device.

32. The first mobile device of claim 30, wherein the first mobile device and the second device are devices associated with a particular user, wherein the first mobile device and the second device communicate with a server, the server for providing cloud synchronization services for the first mobile device and the second device.

33. The first mobile device of claim 30, wherein the received address is an address associated with a recent task performed on the second device, wherein the recent task is one of a search in a web browser and a communication with a contact.

34. The mobile device of claim 30, wherein the program further comprises sets of instructions for:

identifying a location of the first mobile device;

storing past locations of the first mobile device and the received address from the second device; and

predicting at least one future destination of the first mobile device based on a current location of the first mobile device and the stored, past locations and the received address from the second device, wherein presenting the received address as a potential destination for the first mobile device is based on the prediction of the received address as a future destination of the first mobile device.

35. The first mobile device of claim 34, wherein the set of instructions for predicting at least one future destination comprises a set of instructions for calculating a probability of the at least one future destination being an actual destination, wherein the set of instructions for presenting the received address comprises a set of instructions for presenting the predicted destinations ordered according to the calculated probability.

36. The first mobile device of claim 35, wherein the set of instructions for predicting at least one future destination comprises a set of instructions for updating the calculated probability, wherein the set of instructions for presenting the received address comprises a set of instructions for updating the presentation based on the updated calculated probability.

37. A method for providing information about potential destinations for a first device, the method comprising:

receiving an address from a second device;

receiving instructions to open a map application on the first device; and

presenting the received address as a potential destination for the first device.

38. The method of claim 37, wherein presenting the received address comprises presenting the received address in a search display area of the map application, the search display area for displaying prior location searches that the map application has performed on the first device.

39. The method of claim 37, wherein the first and second devices are devices associated with a particular user, wherein the first and second devices communicate with a server, the server for providing cloud synchronization services for the first and second devices.

40. The method of claim 37, wherein the received address is an address associated with a recent task performed on the second device, wherein the recent task is one of a search in a web browser and a communication with a contact.