Google Inc.

Dale Kris Hawkins

Tushar Udeshi

Andrew Robert Kirmse

Guang Yu Yang

James Anthony Guggemos

Pablo Bellver

Thomas Carl Stamm

Tom Carl Stamm

Emil Constantin Praun

Keir Banks Mierle

Gokay Baris Gultekin

Bill Connor

Brian Edmond Brewington

David Singleton

Brian Gammon Brown

Steve Okamoto

Bryce Stout

Gregory Michael Blevins

Erez Louider

Marc Stogaitis

Ronghui Zhu

David Hawkey

Guang Yang

James A Guggemos

David James Hawkey

A computing system is described that obtains, based at least in part on information included in at least one previous communication associated with a user of a computing device, an indication of a future location and a future time and event information associated with the future location and the future time. The computing system obtains a duration of time for the user to travel from a current location of the computing device to the future location, and, based at least in part on the duration of time, obtains a departure time at which the user is predicted to need to depart from the current location in order to arrive at the future location by an arrival time based on the event. The computing system outputs, for transmission to the computing device, an indication associated with the event and including information indicative of the departure time.

Presenting information for a current location or time

The systems and techniques disclosed herein provide the ability to present, via a user interface, an indication of a geographic location to a user, determining that the geographic location corresponds to an address included in contact information for one of several contacts of the user, the contact information further including a name; receive, via the user interface, an indication that the geographic location is to be associated with the name included in the contact information; generate a location label for the geographic location, using the name included in the contact information; and outputting an indication of the location label.

Labeling locations based on contact information

Computer-implemented methods for generating and executing user-based standing queries are provided. In one aspect, a method includes determining whether to generate a notification based on a user-based query and geographical context. The method also includes filtering the notification through explicit or inferred filter criteria. Systems and machine-readable media are also provided.

Automatic user-based query generation and execution

The systems and techniques disclosed herein provide the ability to determine locations visited by a user and associate relevant location labels with the locations visited based on contact information. In some examples, a location label can be applied based on a match between a location visited and information stored in a user's contact list. In other examples, a user can efficiently designate a contact and location label to be associated with a location visited. In still other examples, if a location visited by a user is not listed in the user's contact list, but is otherwise known to the system, the location visited can be appropriately labeled and the corresponding contact in the user's contact list can be updated to include the location visited.

Labeling visited locations based on contact information

Techniques are disclosed herein that generally involve storing a historical record of a user's maps searches (a maps history), and providing a user with relevant information about elements in their maps history based on the location of a mobile device associated with the user. Such elements can include generic queries, specific queries, direction queries, click entries, places, and so forth. In some examples, the mobile device's location is provided to a server, which in turn processes the user's maps history to determine which elements from the maps history may be relevant to the mobile device's current location. Elements that are determined to be of possible relevance, and/or information relating thereto, can then be presented to the user, in many instances decreasing the time and effort required for the user to locate map-based information for which they are searching.

Determining attractions based on location history data

Example techniques and systems include generating cluster information to consolidate multiple locations. In one example, a method includes receiving, at a computing device, a plurality of location identifiers corresponding to a plurality of locations at which a mobile computing device was previously located, defining, by the computing device, a plurality of geographic regions based at least in part on the plurality of location identifiers, wherein each of the plurality of geographic regions defines a physical area in which at least one of the plurality of locations is located, selecting, by the computing device, a subset of the plurality of geographic regions based on respective distances between a current location of the mobile computing device and a respective reference point within each of the geographic regions, and outputting, by the computing device and for display, an indication of the subset of the plurality of geographic regions.

Adaptive clustering of locations

A computing system is described that can provide a user with alerts based on traffic information related to the user's expected travel route. In some embodiments, a user can be alerted if a traffic delay exists on the user's expected travel route. In other embodiments, a user can be alerted when their usual bus or train is delayed. In further embodiments, a user can be alerted when traffic on an expected route to the user's next event location might impact the user's ability to arrive at that location on time.

Contextual traffic or transit alerts

In one example, a method includes determining, based on first motion data, that a change in an angle of a mobile computing device relative to gravity satisfies a threshold amount of change, and, responsive to determining that the change in the angle satisfies the threshold amount of change, initiating, at a first position of the mobile computing device, storage of second motion data, wherein the first position is a reference position. The method may also include determining, based on an external signal, a second position of the mobile computing device, wherein the second position is a current position of the mobile computing device that is different from the reference position, and, responsive to determining the second position of the mobile computing device, determining, based on the second motion data and the current position, the reference position of the mobile computing device.

Automated detection of vehicle parking and location

Growing community of inventors

Erie, CO, United States of America

Dale Kris Hawkins