Abstract:
Step detection accuracy in mobile devices is increased by determining whether swinging is taking place. According to the invention, swinging can be detected using threshold detection, Eigen analysis, hybrid frequency analysis, and/or gyroscope-based analysis, for example. The determination that swinging is (or may be) occurring can impact how the mobile device reports detected steps for step detection. A count of missteps and/or a level of certainty, based on swing detection, can be provided with a step count.
Abstract:
Techniques for providing a user with an augmented virtuality (AV) experience are described herein. An example of a method of providing an AV experience includes determining a location of a mobile device, determining a context based on the location, obtaining AV object information, displaying the AV object information in relation to the context, detecting an interaction with the context, modifying the AV object information based on the interaction, and displaying the modified AV object information. The context may include weighting information. The weighting information may be based on Received Signal Strength Indication (RSSI) or Round-Trip Time (RTT) data. The weighting information may be associated with a composition of a physical object in the context. A user gesture may be received, and the AV object information may be modified based on the received gesture information.
Abstract:
In one implementation, a method may comprise: storing a user profile indicative of at least one attribute of a user of a mobile station; determining a measurement value based, at least in part, on a signal from at least one sensor on the mobile station; and estimating a location of the mobile station based, at least in part, on an association of the at least one attribute and the measurement value with a context parameter map database.
Abstract:
Various techniques are provided for identifying a position uncertainty of a mobile device, such as, based, at least in part, on a measure of potential hindrance of an estimated trajectory. For example, an example method may comprise estimating a trajectory of the mobile device within a particular environment, determining a measure of potential hindrance for at least a portion of the trajectory based, at least in part, on an electronic map that is indicative of a presence or an absence of one or more obstacles, and presenting an indication of a position uncertainty to a user of the mobile device. The position uncertainty may be based, at least in part, on the measure of potential hindrance.
Abstract:
Various methods, apparatuses and/or articles of manufacture are provided which may be implemented to estimate a trajectory of a mobile device within an indoor environment. In some embodiments, the trajectory may be estimated without the use of any signal-based positioning information. For example, a mobile device may estimate such a trajectory based, at least in part, on one or more sensor measurements obtained at the mobile device, and further affect the estimated trajectory based, at least in part, on one or more objects identified in an electronic map of the indoor environment.
Abstract:
In one implementation, a method may comprise: storing a user profile indicative of at least one attribute of a user of a mobile station; determining a measurement value based, at least in part, on a signal from at least one sensor on the mobile station; and estimating a location of the mobile station based, at least in part, on an association of the at least one attribute and the measurement value with a context parameter map database.
Abstract:
Disclosed are systems, methods and devices for application of measurements obtained from a compass or magnetometer in estimating a location of a mobile device. In specific implementations, expected signatures of local magnetic fields at locations are provided to a mobile device as positioning assistance data. In other implementations, magnetic measurements obtained by multiple mobile devices at identifiable locations in an indoor area may be combined for deriving expected signatures of local magnetic fields for use in positioning assistance data.