Apple Inc.

Leonardo A Soto Matamala

Ronald Keryuan Huang

Cherif Jazra

Bharath Narasimha Rao

Scott M Herz

Lukas Michael Marti

Xiaoyuan Tu

Tad Shimada

Jay N Bruins

Bharath Narashima Rao

Applications may be tagged with location data when they are used. Mobile device may anonymously submit application usage data. Aggregated application usage data from many mobile devices may be analyzed to determine applications that are particularly relevant to a given location (i.e., exhibiting a high degree of localization). Analysis may include determining the application usage intensity, whether hotspots exist or not at a given location, the spatial entropy of a particular application, the device populations in a particular area, etc. Based on the localized application analysis, applications may be ranked according to local relevance, and, based on this ranking, application recommendations may be provided to a user.

App recommendation using crowd-sourced localized app usage data

A digitally stored map can indicate the signal quality for each of the map's regions. A device can determine its location, speed, and direction using global positioning system (GPS) and other sensors. Based on this information, the mobile device can predict a field of locations within which the device will probably be located within a specified future time frame. Based on both the information indicating signal quality and the probable future field of locations, the device can estimate a moment at which the device will probably begin to suffer from low-quality or absent signal. Using this prediction, the device can proactively perform a variety of anticipatory remedial actions. For example, the device can begin allocating a greater portion of currently available wireless network communication bandwidth to the reception of data packets that represent content that is being streamed to the device, so that the device can proactively buffer those packets.

Location-assisted service capability monitoring

Mobile devices can provide app recommendations that are relevant to a location of interest. A localized app recommendation can be triggered (e.g., by a mobile device coming within a threshold distance of an application hotspot or some other user action). A location of interest can be determined. The location of interest can be the current location of the mobile device or another location (e.g., the destination in a mapping app). Using the location of interest, a localized application ranking database with app hotspot data can be queried with location data representing the location of interest. App recommendations can be received and displayed on the mobile device. Icons for apps that are relevant to the location of interest can be visually distinguished from other apps.

Mobile device with localized app recommendations

Using various functionalities of electronic devices such as applications that gather location information to provide a service to the user can come at the cost of significant power consumption, and consequently battery drainage. A data sharing system enables the creation of a network of participant devices where participant devices in the network can take turns in collecting and sharing data with the rest of the participant devices in the network. The one or more participant devices can share the obtained data through Bluetooth&#xae; low energy (BTLE) or other low consumption channel, so that the ensemble of participant devices could have better battery life, higher availability, and/or better accuracy, compared to each device having to individually obtain the data.

Dynamic device collaboration

Location assisted service capability monitoring

Apps may be tagged with location data when they are used. Mobile device may anonymously submit app usage data. Aggregated app usage data from many mobile devices may be analyzed to determine apps that are particularly relevant to a given location (i.e., exhibiting a high degree of localization). Analysis may include determining the app usage intensity, whether hotspots exist or not at a given location, the spatial entropy of a particular app, the device populations in a particular area, etc. Based on the localized app analysis, apps may be ranked according to local relevance, and, based on this ranking, app recommendations may be provided to a user.

Growing community of inventors

Los Altos, CA, United States of America

Leonardo A Soto Matamala