Apple Inc.

Jahshan A Bhatti

Brent Michael Ledvina

Robert William Mayor

David R Stites

Kevin Duffy

Kevin P McLaughlin

Lukas Michael Marti

Brian Stephen Smith

Adam A Sonnanstine

John L Blatz

Joseph E Meyer

Joao Pedro Lacerda

Alexander D Palmer

Wei Zhang

Robert W Brumley

Chiu Ngok E Wong

David Benjamin Millman

Jasvinder Singh

Wei Kong

Techniques for suggesting accessory devices controlled by an application executing on a mobile device are disclosed. A method includes measuring one or more sensor values using one or more sensors of a mobile device and the one or more sensor values are determined from one or more signals emitted by a first one or more accessory devices. An area of a physical space for the first one or more accessory devices can be determined based on the one or more sensor values. A second one or more accessory devices associated with the same area as the first one or more accessory devices can be suggested to a user.

Using in-home location awareness

Embodiments are disclosed for a feature-based simultaneous localization and mapping (SLAM) system and method that generates radio maps for environments that are not accessible for surveying. More accurate radio maps are generated for an unsurveyed environment by determining a best estimate of a mobile device state from harvested traced data that maximizes a posterior probability of the mobile device state given measurements, landmarks and loop constraints.

Feature-based slam

Techniques are disclosed for predictive media streaming using microlocation. Microlocations of a mobile device can be determined by measuring one or more sensor values at one or more times, the one or more sensor values are determined from one or more signals emitted by a corresponding one or more signal sources. Streaming events can be stored at the mobile device. Each streaming event may include a destination device for playing media and a cluster location, the cluster location corresponding to sensor values that are spatially near each other. A selection of a media item is detected and one or more current sensor values are measured. A current cluster location can be identified using the one or more current sensor value. The current cluster location and the streaming events can identify a particular destination device for playing the selected media item.

Predictive routing based on microlocation

A method comprising: receiving a radio map of an indoor venue using survey data collected by a survey device positioned throughout the venue, the radio map including a boundary; receiving harvest data from a mobile device, wherein at least some of the harvest data are obtained by the mobile device while the mobile device is positioned at locations that are outside of the boundary; determining, based on the harvest data, a trajectory of the mobile device, wherein at least some of the trajectory resides outside of the boundary; identifying one or more locations on or proximate to the trajectory; and extending the radio map using the survey data and the one or more identified locations, wherein the extended radio map is defined at least in part by an extension of the boundary to encompass the one or more identified locations.

Extending a radio map

Techniques for suggesting accessory devices controlled by an application executing on a mobile device are disclosed. A method includes measuring one or more sensor values to determine a data point at each of a plurality of first times, associating an accessory device with each of the data points, clustering the data points within a threshold distance of each other to create a plurality of clusters. The method also includes, after clustering the data points, measuring one or more sensor values to determine one or more current data points at a second time, determining that one or more current data points at the second time corresponds to a first cluster of the plurality of clusters, identifying a first accessory device associated with one or more of the data points in the first cluster, and providing a message using the application.

A method for identifying a suggested application on a mobile device is disclosed. The method includes detecting an event, determining a first location of the mobile device, identifying that the first location is within a first location region of a plurality of predetermined location regions, and then measuring one or more sensor values at one or more times. The measured sensor values may then be used to create a first-data point. In response to identifying the first location region, a plurality of clusters of data points may be retrieved. A first cluster of the plurality of clusters corresponding to the first data point may then be identified. The method may further include identifying a set of one or more applications, and then providing a message to the user based on the identified set of one or more applications.

Proactive actions on mobile device using uniquely-identifiable and unlabeled locations

The subject system aggregates, or stitches, multiple component channel estimates to generate an aggregated wideband channel estimate that can be used to determine more accurate time of arrival estimations than those determinable from the individual component channel estimates. The subject system also provides for multipath detection on a single channel or an aggregated channel that may be used to facilitate an accurate time of arrival estimation. For example, information derived from the multipath detection may be used to supplement and/or enhance a time of arrival estimation algorithm. The subject system also provides a sounding protocol that allows devices to perform one or more signal exchanges to facilitate generating the aggregated wideband channel estimate and/or to facilitate performing the multipath detection. The protocol allows the devices to perform signal exchanges over one or more channels within a coherence time, and also provides for security mechanisms as well as failure recovery.

Time of arrival estimation

A mobile device can identify its physical location without explicit knowledge of physical coordinates, but instead using sensor measurements dependence on distance, e.g., signal strength from a Wi-Fi router. Sensor measurements can be used to determine the mobile device is at a same physical location as a previous measurement. For example, numerous measurements of sensor values can form data points that are clustered in sensor space, where a cluster of data points in sensor space corresponds to a physical cluster of physical positions in physical space. A current physical location of the mobile device can be determined by identifying which cluster of sensor positions the current measurements correspond. To identify the cluster of sensor positions, a probability can be determined for each cluster based on a sensor distance between the current measurement and a representative data point of the cluster and a kernel function.

Determining location of mobile device using sensor space to physical space mapping

A method for identifying a location of a mobile device is disclosed. The method includes during each of a plurality of instances of time: measuring one or more signal properties of one or more other devices across a time interval; obtaining an identifier from each of the one or more other devices; creating a data point to include the one or more signal properties; and storing the data point in a database. The method further includes analyzing the plurality data points in the database to determine clusters of data points; detecting an event at an input device of the mobile device; measuring one or more new signal properties of one or more of the plurality of other devices at one or more new times; creating a new data point from the one or more new signal properties; and identifying a first cluster corresponding to the new data point.

Growing community of inventors

San Jose, CA, United States of America

Jahshan A Bhatti