Abstract:
Crowd-sourced localized application usage data is collected from mobile devices at a usage location and sent to a network-based service. The network-based service analyzes the data to determine a single most relevant application correlated to the usage location. Once the most relevant application is determined, a recommendation for the application is sent to client devices operating at the usage location. In some implementations the data is processed to determine whether the usage location is a chained venue, a large venue or an event. Once the usage location has been determined, the most relevant application can be selected for recommendation.
Abstract:
Collocated access point (AP) harvest data is combined with accurate location-tagged harvest data to improve access point location estimates and to estimate the location of access points that could not be previously estimated.
Abstract:
Crowd-sourced location data from client devices is processed using enhanced filtering techniques in non-realtime by a centralized server process to improve the accuracy and reliability of georeferenced geodata. At a server computer, enhanced filtering techniques make use of future information to improve georeferencing of the geodata. In some implementations, the server computer can be configured to implement batch processing of raw GNSS data and other crowd-sourced location data (e.g., wireless scan data, inertial sensor data) using, for example, a smoothing filter or batch estimator. Augmentation data (e.g., satellite ephemeris data, clock offset and ionospheric delay) and sensor data independent of client devices can also be used by the server computer to augment the crowd-sourced location data to further improve georeferencing of geodata.
Abstract:
Methods, program products, and systems for selective location determination are described. A mobile device can determine a location of the mobile device using various techniques. When there is a conflict between the locations determined using different techniques, the mobile device can select a most trustworthy location from the locations, and designate the most trustworthy location as a current location of the mobile device. The mobile device can determine a first location of the mobile device (e.g., a coarse location) using a cell identifier (cell ID) of a cellular network. The mobile device can determine a second location of the mobile device (e.g., a fine location) using one or more media access control (MAC) addresses of a WLAN. The first location and second location can be associated with confidence values that can indicate trustworthiness of the first location and second location.
Abstract:
Methods, program products, and systems of location estimation using a probability density function are disclosed. In general, in one aspect, a server can estimate an effective altitude of a wireless access gateway using harvested data. The server can harvest location data from multiple mobile devices. The harvested data can include a location of each mobile device and an identifier of a wireless access gateway that is located within a communication range of the mobile device. The server can calculate an effective altitude of the wireless access gateway using a probability density function of the harvested data. The probability density function can be a sufficient statistic of the received set of location coordinates for calculating an effective altitude of the wireless access gateway. The server can send the effective altitude of the wireless access gateway to other mobile devices for estimating altitudes of the other mobile devices.
Abstract:
Methods, program products, and systems for multi-tier geofence detection are disclosed. In general, in one aspect, a mobile device can be configured to perform a task when the mobile device enters a geographic region. The mobile device can monitor a current location using a multi-tier approach. A baseband subsystem can monitor a coarse location of the mobile device using various course location parameters, such as a mobile country code (MCC), a location area code (LAC), or a cell identifier (cell ID), as the mobile device moves closer to the geographic region. Upon determining that the mobile device is in a cell that intersects the geographic region, the baseband subsystem can transfer the monitoring to the application subsystem. The task can be performed when the application subsystem determines that the mobile device is currently located in the geographic region.
Abstract:
Methods, program products, and systems of location estimation using a probability density function are disclosed. In general, in one aspect, a server can estimate an effective altitude of a wireless access gateway using harvested data. The server can harvest location data from multiple mobile devices. The harvested data can include a location of each mobile device and an identifier of a wireless access gateway that is located within a communication range of the mobile device. The server can calculate an effective altitude of the wireless access gateway using a probability density function of the harvested data. The probability density function can be a sufficient statistic of the received set of location coordinates for calculating an effective altitude of the wireless access gateway. The server can send the effective altitude of the wireless access gateway to other mobile devices for estimating altitudes of the other mobile devices.
Abstract:
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® 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.
Abstract:
A method for determining current local time for a wireless communication device is provided. The method can include a wireless communication device receiving a message sent by a network entity. The message can include location information indicative of a location associated with a time zone in which a serving cell for the wireless communication device is located. The method can further include the wireless communication device extracting the location information from the message; using the location information to determine the time zone; and determining a current local time based on the time zone.
Abstract:
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.