Apple Inc.

International Business Machines Corporation

Jason Dere

Ronald Keryuan Huang

Robert William Mayor

Lukas Michael Marti

Glenn Donald MacGougan

Yefim Grosman

Morgan J Grainger

Daniel Martin DeKimpe

Nathan Gevaerd Colossi

Steven Sit

Glenn Donald Macgougan

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.

Altitude estimation using a probability density function

A method for collecting the information from the mobile devices for producing real-time traffic data is provided. The process ensures that the collection of data from a mobile device to be non-intrusive to the user of the mobile device by using only communication channels that are already open and by using only Global Positioning System (GPS) data from an application that is already running on the mobile device. The mobile device will participate in the data collection only if its battery power is above certain threshold level or if its battery is currently being charged. The method will not let a mobile device participate in the data collection process if the mobile device has already provided more than a threshold amount of data to the traffic data collection during a particular period of time. The method let only mobile devices that are moving beyond certain speed to participate.

Harvesting traffic information from mobile devices

Methods, program products, and systems for multi-tier detection of a geofence 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-tiered approach. A baseband subsystem can monitor a coarse location of the mobile device using a CDMA system identifier, a CDMA network identifier, a CDMA zone identifier, or a CDMA base station identifier, in that order, as the mobile device moves closer to the geographic region. The baseband subsystem can notify an application subsystem when the mobile device is in a cell that intersects the geographic region. The application subsystem can perform the task upon notification.

Multi-tiered detection of a geofence

In some implementations, a location of a mobile device can be determined by calculating an average of the locations of wireless signal transmitters that have transmitted signals received by the mobile device. In some implementations, locations are weighted with coefficients and the average is a weighted average. In some implementations, the locations of the wireless signal transmitters are determined based on identification information encoded in the wireless signals received by the mobile device. The identification information can include an identifier for a wireless signal transmitter. The identification information can include characteristics of the received wireless signal that can be used to identify wireless signal transmitters. In some implementations, identification information from one signal can be combined with identification information from another signal to determine a location of a wireless transmitter.

Neighbor cell location averaging

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 location 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 location 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 location of the wireless access gateway. The server can send the effective location of the wireless access gateway to other mobile devices for estimating locations of the other mobile devices.

Location estimation using a probability density function

A mobile device can store a set of first CDMA identifiers including, for example, system identifiers, network identifiers, or zone identifiers. Each first CDMA identifier can be associated with a first geographic location. The mobile device can determine a current location by matching a current first CDMA identifier with a stored first CDMA identifier. If a user desires a current location that has finer granularity, the mobile device can retrieve a set of second CDMA identifiers including, for example, base station identifiers. Each second CDMA identifiers can be associated with a second geographic location that has a finer granularity than that of the first geographic location. The mobile device can match a current second CDMA identifier from the retrieved second CDMA identifiers and designate the second geographic location associated with the matching second CDMA identifier as the current location that has the finer granularity.

Multiple granularity location determination

Methods, program products, and systems of location estimation using multiple wireless access gateways are disclosed. In general, in one aspect, a mobile device can scan and detect multiple wireless access gateways. The mobile device can determine an initial estimate of distance between the mobile device and each wireless access gateway. The mobile device can receive, from a server, location data of the detected wireless access gateways. The location data can include an estimated location of each wireless access gateway, an uncertainty of the estimated location, and a reach of each wireless access gateway. The mobile device can assign a weight to each estimated location using the uncertainty, the reach, and the initial estimate. The mobile device can estimate the location of the mobile device using the weighted locations.

Mobile device location estimation

A system, method, and program for improving the performance for SQL queries. Multidimensional metadata associated with a cube model metadata object is obtained. One or more summary tables to be built are automatically identified based on the obtained multidimensional metadata. One or more indexes to create are automatically identified based on the obtained multidimensional metadata.

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San Jose, CA, United States of America

Jason Dere