Abstract: A mobile device can provide predictive user assistance based on various sensor readings, independently of or in addition to a location of the mobile device. The mobile device can determine a context of an event. The mobile device can store the context and a label of the event on a storage device. The label can be provided automatically by the mobile device or by the external system without user input. At a later time, the mobile device can match new sensor readings with the stored context. If a match is found, the mobile device can predict that the user is about to perform the action or recognize that the user has performed the action again. The mobile device can perform various operations, including, for example, providing user assistance, based on the prediction or recognition.

Abstract: Systems, methods, and program products for providing services to a user by a mobile device based on the user's daily routine of movement. The mobile device determines whether a location cluster indicates a significant location for the user based on one or more hints that indicate an interest of the user in locations in the cluster. The mobile device can perform adaptive clustering to determine a size of area of the significant location based on how multiple locations converge in the location cluster. The mobile device can provide location-based services for calendar items, including predicting a time of arrival at an estimated location of a calendar item. The mobile device can provide various services related to a location of the mobile device or a significant location of the user through an application programming interface (API).

Abstract: A device in an automated environment can detect patterns in the user's interactions with accessories in the automated environment and can provide feedback to the user based on the patterns. Examples include: suggesting automation of particular actions based on the patterns; suggesting actions that conform to the pattern when the user performs part of the pattern; or suggesting changes to a pattern to conform to a preferred pattern. A state of the group of accessory devices can be changed together based on the pattern of accessory state changes for the group of accessory devices.

Abstract: Systems, methods, and program products for providing services to a user by a mobile device based on the user's daily routine of movement. The mobile device determines whether a location cluster indicates a significant location for the user based on one or more hints that indicate an interest of the user in locations in the cluster. The mobile device can perform adaptive clustering to determine a size of area of the significant location based on how multiple locations converge in the location cluster. The mobile device can provide location-based services for calendar items, including predicting a time of arrival at an estimated location of a calendar item. The mobile device can provide various services related to a location of the mobile device or a significant location of the user through an application programming interface (API).

Abstract: A method includes determining a routing graph based on a map, wherein the routing graph represents locations from the map; determining a routing horizon based on the routing graph, wherein the routing horizon defines a portion of the routing graph that is usable for routing; determining a cost-action structure that includes, for each location of the routing horizon, a cost-to-go value for travel from a respective location from the routing horizon to a destination, wherein the cost-to-go values implicitly describe an optimal route for travel from each of the respective locations from the routing horizon to the destination; receiving, from an autonomous agent, a request that specifies one of the locations from the routing horizon; and providing, to the autonomous agent, information from the cost-action structure based on the specified location from the routing horizon.

Abstract: A method includes determining a first route from a first location to a second location using a first map that includes first map elements, wherein the first route includes a series of the first map elements from the first map. The method also includes matching the series of the first map elements from the first route to second map elements from a second map to define a subset of the second map elements, and determining a second route from the first location to the second location using the subset of the second map elements. The second route is constrained to the subset of the second map elements and the second route includes a series of the second map elements from the subset of the second map elements. The method also includes outputting information describing the second route for at least one of storage or display.

Abstract: A user interface enables a user to calibrate the position of a three dimensional model with a real-world environment represented by that model. Using a device's sensor, the device's location and orientation is determined. A video image of the device's environment is displayed on the device's display. The device overlays a representation of an object from a virtual reality model on the video image. The position of the overlaid representation is determined based on the device's location and orientation. In response to user input, the device adjusts a position of the overlaid representation relative to the video image.

Abstract: Methods, systems, and computer program products for determining transit routes through crowd-sourcing, for determining an estimated time of arrival (ETA) of a vehicle of the transit route at a given location, and for providing predictive reminders to a user for catching a vehicle of the transit route. A server receives signal source information about wireless signal sources detected by user devices, including information about a first wireless signal source detected by some devices. The server determines that the first wireless signal source is moving. The server determines that the first wireless signal source is associated with a public transit route upon determining that the signal source information satisfies one or more selection criteria. The server stores information associating the first wireless signal source with the public transit route as transit movement data corresponding to the public transit route.

Abstract: Methods, systems, and computer program products for determining transit routes through crowd-sourcing, for determining an estimated time of arrival (ETA) of a vehicle of the transit route at a given location, and for providing predictive reminders to a user for catching a vehicle of the transit route. A server receives signal source information about wireless signal sources detected by user devices, including information about a first wireless signal source detected by some devices. The server determines that the first wireless signal source is moving. The server determines that the first wireless signal source is associated with a public transit route upon determining that the signal source information satisfies one or more selection criteria. The server stores information associating the first wireless signal source with the public transit route as transit movement data corresponding to the public transit route.

Abstract: An automated environment can include an accessory device that operates according to an automation rule, to take a prescribed action when a triggering condition occurs. A controller device for the automated environment can determine a user's regular routine and can detect when the user is deviating from the regular routine. The controller device can communicate with accessory devices in the automated environment to modify their behavior relative to the automation rules.

Abstract: Systems, methods, and program products for providing services to a user by a mobile device based on the user's daily routine of movement. The mobile device determines whether a location cluster indicates a significant location for the user based on one or more hints that indicate an interest of the user in locations in the cluster. The mobile device can perform adaptive clustering to determine a size of area of the significant location based on how multiple locations converge in the location cluster. The mobile device can provide location-based services for calendar items, including predicting a time of arrival at an estimated location of a calendar item. The mobile device can provide various services related to a location of the mobile device or a significant location of the user through an application programming interface (API).

Abstract: A method includes capturing images at a device and analyzing the images at the device using a first analysis model to obtain information regarding an observed object that corresponds to a predetermined object. The method also includes determining whether the information regarding the observed object is consistent with stored mapping information, and, in response to determining that the information regarding the observed object is not consistent with the stored mapping information, modifying the stored mapping information based on the observed object.

Abstract: Systems, methods, and program products for providing services to a user by a mobile device based on the user's daily routine of movement. The mobile device determines whether a location cluster indicates a significant location for the user based on one or more hints that indicate an interest of the user in locations in the cluster. The mobile device can perform adaptive clustering to determine a size of area of the significant location based on how multiple locations converge in the location cluster. The mobile device can provide location-based services for calendar items, including predicting a time of arrival at an estimated location of a calendar item. The mobile device can provide various services related to a location of the mobile device or a significant location of the user through an application programming interface (API).

Abstract: A method includes obtaining a first map element from a first map, identifying second map elements from a second map based on locations of the second map elements relative to the first map element, and identifying first and second point on the second map elements based on proximity to beginning and ending points of the first map element. One or more of the second map elements define a corresponding portion of the second map between the first point and the second point. The method also includes determining a registration score for the first map element relative to the corresponding portion of the second map, and in response to determining that the registration score indicates a match between the first map element and the corresponding portion of the second map, defining registration information that describes a relationship between the first map element and the corresponding portion of the second map.

Abstract: A method includes determining a first route from a first location to a second location using a first map that includes first map elements. The first route includes a series of the first map elements. The method also includes determining a second route from the first location to the second location using a second map by matching the series of the first map elements from the first route to second map elements from the second map. The method also includes monitoring a current location of a device, determining that the current location of the device does not correspond to any of the first map elements from the series of the first map elements, and determining a third route from the current location of the device toward the second location using the second map in response to determining that the current location does not correspond to any of the first map elements.

Abstract: A user interface enables a user to calibrate the position of a three dimensional model with a real-world environment represented by that model. Using a device's sensor, the device's location and orientation is determined. A video image of the device's environment is displayed on the device's display. The device overlays a representation of an object from a virtual reality model on the video image. The position of the overlaid representation is determined based on the device's location and orientation. In response to user input, the device adjusts a position of the overlaid representation relative to the video image.

Abstract: A method includes capturing images at a device and analyzing the images at the device using a first analysis model to obtain information regarding an observed object that corresponds to a predetermined object. The method also includes determining whether the information regarding the observed object is consistent with stored mapping information, and, in response to determining that the information regarding the observed object is not consistent with the stored mapping information, modifying the stored mapping information based on the observed object.

Abstract: Systems, methods, and program products for providing services to a user by a mobile device based on the user's daily routine of movement. The mobile device determines whether a location cluster indicates a significant location for the user based on one or more hints that indicate an interest of the user in locations in the cluster. The mobile device can perform adaptive clustering to determine a size of area of the significant location based on how multiple locations converge in the location cluster. The mobile device can provide location-based services for calendar items, including predicting a time of arrival at an estimated location of a calendar item. The mobile device can provide various services related to a location of the mobile device or a significant location of the user through an application programming interface (API).

Abstract: A user interface enables a user to calibrate the position of a three dimensional model with a real-world environment represented by that model. Using a device's sensor, the device's location and orientation is determined. A video image of the device's environment is displayed on the device's display. The device overlays a representation of an object from a virtual reality model on the video image. The position of the overlaid representation is determined based on the device's location and orientation. In response to user input, the device adjusts a position of the overlaid representation relative to the video image.

Abstract: A mobile device can provide predictive user assistance based on various sensor readings, independently of or in addition to a location of the mobile device. The mobile device can determine a context of an event. The mobile device can store the context and a label of the event on a storage device. The label can be provided automatically by the mobile device or by the external system without user input. At a later time, the mobile device can match new sensor readings with the stored context. If a match is found, the mobile device can predict that the user is about to perform the action or recognize that the user has performed the action again. The mobile device can perform various operations, including, for example, providing user assistance, based on the prediction or recognition.