Abstract: Techniques of delivering location data are described. A location server can receive, from a mobile device, a request for location data for determining a location of the mobile device at a venue. The request can include an estimated location of the mobile device. The location server can provide to the mobile device coarse location data for each venue that is located within a threshold distance to the estimated location of the mobile device. The coarse location data can include a list of coarse tiles at each venue, and parameters of a probability distribution function for determining in which tile of the venue the mobile device is located based on signals detected by the mobile device. The location server can the provide location fingerprint data associated with the tile and neighboring tiles to the mobile device. The mobile can use the location fingerprint data to determine a more detailed location.

Abstract: A mobile device can be in multiple states of location determination. In each state, the mobile device can use a distinct subsystem to determine a location. A state machine of the mobile device can manage the states, including determining which state the mobile device is in and whether a transition between the states has occurred. A transition can be triggered by a sensor of the mobile device and confirmed by another sensor of the mobile device. When the state machine detects a transition, the mobile device can switch location determination from one subsystem to another subsystem, and change a map user interface to one that is best suited for the new subsystem.

Abstract: Techniques for lifestyle-based social groups are described. A user device can learn movement patterns of the user device. Based on the movement pattern, and a user activity history, a computer system can determine a lifestyle of a user, or a meaning of a location. The system can create a social group based on the lifestyle and the meaning of location. The system can designate the lifestyle or meaning as a theme of the social group. The social group can be an ad hoc social network. For example, the social group can be created without an explicit user request, can be anonymous, and can be lifestyle and location based.

Abstract: Methods, program products, and systems for monitoring a location fingerprint database are described. A location fingerprint database can store location data associated with multiple signal sources. A mobile device can use signals of the signal sources and the location data to determine a current location. A location server can monitor the location fingerprint database, including detecting if any one of the signal sources has moved or otherwise becomes unsuitable for location determination.

Abstract: A location of a mobile device in a venue can be estimated by using a state space estimator to determine candidate locations of the mobile device at a first time point based on previous candidate positions conditioned upon an observation of one or more environmental variables. A second observation is received at a second time point, and the state space estimator performs a propagation step to determine the candidate locations at the second time point based on the candidate locations at the first time point and the second observation. The propagation step includes a plurality of sub-propagation steps in which a time length between the sub-propagation steps is a fraction of the time length between the first and second time points, and at each sub-propagation step each candidate location is propagated according to a stochastic process. The location of the mobile device at the second time point is determined based on the candidate locations at the second time point.

Abstract: Methods, program products, and systems for using a location fingerprint database to determine a location of a mobile device are described. A mobile device can use a location fingerprint database to determine the location where GPS signals are unavailable. A server can generate location fingerprint data for the database. The server can generate the location fingerprint data using crowd sourcing, using known locations of signal sources, or both. The server can receive, from a sampling device, measurements of environment variables, e.g., signals from a signal source at one or more sampling points. The server can extrapolate, from the received measurements, estimated measurements at one or more locations in a venue. The server can store the extrapolated measurements as location fingerprint data. The server can send the location fingerprint data to a mobile device for determining a location of the mobile device when the mobile device is at the venue.

Abstract: Methods, program products, and systems for using a location fingerprint database to determine a location of a mobile device are described. A mobile device can use location fingerprint data and readings of a sensor to obtain a location observation. The mobile device can use the location observation in a particle filter for determining a location of the mobile device at a venue. Using state of movement of the mobile device and a map of the venue, the mobile device can determine one or more candidate locations of the device. The mobile device can then update the candidate locations using a next observation, and determine a probability density function based on the candidate locations. The mobile device can then present to a user a most probable location as a current location of the device in the venue.

Abstract: Methods, program products, and systems for using a location fingerprint database to determine a location of a mobile device are described. A mobile device can use location fingerprint data received from a server to determine a location of the mobile device at the venue. The mobile device can obtain, from a sensor of the mobile device, a vector of sensor readings, each sensor reading can measure an environment variable, e.g., a signal received by the sensor from a signal source. The mobile device can perform a statistical match between the vector and the location fingerprint data. The mobile device can then estimate a current location of the mobile device based on the statistical match.

Abstract: Techniques of non-intrusive region notification are described. A mobile device can be programmed to trigger an application program when the mobile device enters or exits a region. The region can be defined by various virtual fencing technologies. If, at the time of entry or exit of a region, the mobile device is in a power-saving operating mode, the mobile device can transition to an active operating mode temporarily, register a fence-crossing event (entry or exit of the region) with the application program, and then transition back to the power-saving operating mode. The mobile device can launch the registered application program in response to the mobile device receiving a user input to enter the active operating mode. The application program can provide a user interface associated with the region on a display surface of the mobile device in place of a home screen or other user interface.

Abstract: Techniques of category-based fence are described. A category-based fence can correspond to a group of signal sources instead of a point location fixed to latitude and longitude coordinates. The group of signal sources can represent a category of entities, e.g., a particular business chain. The signal sources can be distributed to multiple discrete locations. A category-based fence associated with the group, accordingly, can correspond to multiple locations instead of a single point location and a radius. Each signal source in the group can be associated with a category identifier unique to the group and uniform among signal sources in the group. The category identifier can be programmed into each signal source. A mobile device can enter the category-based fence by entering any of the discrete locations when the mobile device detects the signal identifier. The mobile device can then execute an application program associated with the category-based fence.

Abstract: Implementations are disclosed for obtaining a range state of a device operating in an indoor environment with radio frequency (RF) signal sources. In some implementations, windowed signal measurements obtained from RF signals transmitted by an RF signal source are classified into range classes that are defined by threshold values obtained from a RF signal propagation model. A range class observation is obtained by selecting a range class among a plurality of range classes based on a percentage of a total number of windowed signal measurements that are associated with the range class. The range class observation is provided as input to a state estimator that estimates a range class that accounts for process and/or measurement noise. The output of the state estimator is provided as input to a state machine.

Abstract: A mobile device can send a request to a server having a plurality of tiles of location data associated with a venue, each tile having location data associated with a portion of the venue, the request including data representing an estimated location of the mobile device. The mobile device can receive a first tile of location data sent from the server, the first tile being associated with a first portion of the venue that includes the estimated location. The mobile device can receive a first sensor reading and determine a first location of the mobile device at the venue using the first sensor reading and the first tile of location data. The mobile device may receive a second tile of location data sent from the server, the second tile being associated with a second portion of the venue. The mobile device may receive a second sensor reading and determine a second location of the mobile device at the venue using the second sensor reading and the second tile of location data.

Abstract: A proximity fence can be a location-agnostic fence defined by signal sources having no geographic location information. The proximity fence can correspond to a group of signal sources instead of a point location fixed to latitude and longitude coordinates. A signal source can be a radio frequency (RF) transmitter broadcasting a beacon signal. The beacon signal can include a payload that includes an identifier indicating a category to which the signal source belongs, and one or more labels indicating one or more subcategories to which the signal source belongs. The proximity fence defined by the group of signal sources can trigger different functions of application programs associated with the proximity fence on a mobile device, when the mobile device moves within the proximity fence and enters and exits different parts of the proximity fence corresponding to the different subcategories.

Abstract: Methods, program products, and systems for reducing a location search space are described. A mobile device, when arriving at a venue, can determine a location of the mobile device using signals from one or more signal sources associated with the venue. The mobile device can use a coarse location estimator to estimate a coarse location of the mobile device at the venue. The mobile device can request, from a server, detailed location data associated with the coarse location. The detailed location data can include location fingerprint data associated with a portion of the venue that includes the coarse location. The mobile device can determine an estimated location that has finer granularity than the coarse location using the location fingerprint data.

Abstract: Techniques of delivering location data are described. A location server can receive, from a mobile device, a request for location data for determining a location of the mobile device at a venue. The request can include an estimated location of the mobile device. The location server can provide to the mobile device coarse location data for each venue that is located within a threshold distance to the estimated location of the mobile device. The coarse location data can include a list of coarse tiles at each venue, and parameters of a probability distribution function for determining in which tile of the venue the mobile device is located based on signals detected by the mobile device. The location server can the provide location fingerprint data associated with the tile and neighboring tiles to the mobile device. The mobile can use the location fingerprint data to determine a more detailed location.

Abstract: Surveying techniques for generating location fingerprint data are described. A mobile device can survey a venue by measuring, at multiple locations at the venue, signals from one or more signal sources. At each location, the mobile device can take multiple measurements of signals. The mobile device can take each measurement at a distinct orientation. The measurements can be used to determine expected measurements of the signals at the venue. Differences between the multiple measurements of signals can be used to determine a variance of the expected measurements. The expected measurements and variance can be designated as location fingerprint data for the venue. The location fingerprint data can be used by mobile devices for determining a location at the venue.

Abstract: A processor-based personal electronic device (such as a smartphone) is programmed to automatically respond to data sent by various sensors from which the user's activity may be inferred. One or more alarms on the device may be temporarily disabled when sensor data indicates that the user is asleep. One or more of the sensors may be worn by the user and remote from the device. A wireless communication link may be used by the device to obtain remote sensor data. Data from on-board sensors in the device—such as motion sensors, location sensors, ambient light sensors, and the like—may also be used to deduce the user's current activity. User data (such as calendar entries) may also be used to determine likely user activity and set alarms accordingly. Biometric data from a second, nearby person may also be used to automatically select certain alarm modes on a first person's device.

Abstract: Methods, program products, and systems for monitoring a location fingerprint database are described. A location fingerprint database can store location data associated with multiple signal sources. A mobile device can use signals of the signal sources and the location data to determine a current location. A location server can monitor the location fingerprint database, including detecting if any one of the signal sources has moved or otherwise becomes unsuitable for location determination.

Abstract: Methods, program products, and systems for using a location fingerprint database to determine a location of a mobile device are described. A mobile device can use a location fingerprint database to determine the location where GPS signals are unavailable. A server can generate location fingerprint data for the database. The server can generate the location fingerprint data using crowd sourcing, using known locations of signal sources, or both. The server can receive, from a sampling device, measurements of environment variables, e.g., signals from a signal source at one or more sampling points. The server can extrapolate, from the received measurements, estimated measurements at one or more locations in a venue. The server can store the extrapolated measurements as location fingerprint data. The server can send the location fingerprint data to a mobile device for determining a location of the mobile device when the mobile device is at the venue.

Abstract: A mobile device can be in multiple states of location determination. In each state, the mobile device can use a distinct subsystem to determine a location. A state machine of the mobile device can manage the states, including determining which state the mobile device is in and whether a transition between the states has occurred. A transition can be triggered by a sensor of the mobile device and confirmed by another sensor of the mobile device. When the state machine detects a transition, the mobile device can switch location determination from one subsystem to another subsystem, and change a map user interface to one that is best suited for the new subsystem.