Abstract:
Technologies for context-based management of wearable computing devices include a mobile computing device and a wearable computing device. The wearable computing device generates sensor data indicative of a location context of the wearable computing device and transmits the sensor data to the mobile computing device. The mobile computing device generates local sensor data indicative of a location context of the wearable computing device and fuses the local sensor data with the sensor data received from the wearable computing device. The mobile computing device determines a context of the wearable computing device based on the fused sensor data. The mobile computing device determines whether an adjustment to the functionality of the wearable computing device is required based on the determined context. The mobile computing device manages the functionality of the wearable computing device in response to determining that an adjustment to the functionality is required.
Abstract:
Systems and techniques for sensor-derived object flight performance tracking are described herein. A set of magnetometer readings may be obtained from a magnetometer included with an object. A local rotation axis of the object may be determined at a time using the set of magnetometer readings. The local rotation axis may describe rotation of the object around a local magnetic target. A global rotation axis may be calculated based on an initial orientation of the object. The global rotation axis may describe a fixed rotation axis of the object during flight in a global coordinate frame, wherein an angle between the global rotation axis and magnetic north remains constant during the flight. An orientation of the object may be determined for the time using the global rotation axis and the local rotation axis of the object at the time.
Abstract:
A controller comprises a communication interface to receive an anchor localization dataset comprising a plurality of anchor range measurements and a processing circuitry to identify a qualified subset of anchor range measurements from the anchor localization dataset, wherein the anchor range measurements in the qualified subset are consistent, select a first anchor range measurement in the anchor localization dataset from outside the qualified subset of anchor range measurements, and add the first anchor range measurement to the qualified subset of anchor range measurements when the first anchor range measurement is consistent with the anchor range measurements in the qualified subset of anchor range measurements.
Abstract:
Embodiments of a mobile station and method for Wi-Fi scan scheduling and power adaption for low-power indoor location are generally described herein. In some embodiments, the mobile station may identify channels, beacon timing and rough signal strength levels of nearby access points (APs) from at least one of a previous full-channel scan or a Wi-Fi fingerprint database and may configure receiver sensitivity based on the rough signal strength levels for receipt of subsequent beacons. The mobile station may wake-up from a low-power state to receive beacons for the nearby access points on the identified channels at times based on the identified beacon timing. The received signal strength indicators (RSSIs) levels of the received beacons may be used for location determination.
Abstract:
A system for locating a mobile device includes an input that accesses a plurality of scans of wireless network access signaling, where the scans indicate received signal measurement results. A similarity measure module executes comparisons between the data of different scans in order to assess the similarity between those scans. The comparisons produce multi-dimensional comparison results. A dimension reduction module reduces dimensionality of the multi-dimensional comparison results to produce a dimension-reduced set of comparison results. A clustering module identifies groupings of similar scans based on the dimension-reduced set of comparison results.
Abstract:
This disclosure is directed to positioning and mapping based on virtual landmarks. A space may include a plurality of signal sources (e.g., wireless access points (APs), cellular base stations, etc.). The space may be virtually divided into a plurality of regions, wherein each region in the space may be associated with a virtual landmark. Virtual landmarks may be identified by a signature comprised of measurements of wireless signals received from the plurality of access points when at the associated region. A device position may be approximated based on signal power magnitude and variance measurements for wireless signals received at the virtual landmark. Devices may employ an algorithm such as, for example, Simultaneous Localization and Mapping (SLAM) for positioning and map creation in the space without the need for GPS signals, specialized signaling equipment, pre-navigation device training, etc. Navigation/mapping may also account for space changes, signal source position changes, etc.
Abstract:
A mobile device includes an inertial navigation system (INS) to measure inertial quantities associated with movement of the device, and estimate a kinematic state associated with the movement based on the measured inertial quantities. The device includes a light receiver to record light beams originating from lights at respective image positions in a sequence of images. The device photogrammetrically determines its position relative to the originating lights based on predetermined real-world positions and corresponding image positions of the lights. The device corrects the estimated kinematic state based on the photogrammetrically determined position, to produce a corrected estimated kinematic state.
Abstract:
Various embodiments are generally directed to techniques to provide location sensing of a virtual map derived from sensors of a computing device moved about an interior of a structure. An apparatus for location sensing includes a processor component; and a refined trajectory generator, an inconsistent constraint identifier for identifier inconsistent constraints used to generate the refined trajectories, and an updated constraint set generator for updating the constraint set to remove the identified inconsistent constraints. Other embodiments are described and claimed.
Abstract:
A method of determining landmarks includes receiving, at a computing system, a plurality of potential landmark measurements and corresponding signal measurements. The method further includes determining, at the computing system, a plurality of landmark candidates from the plurality of potential landmark candidates and corresponding signal measurements. The method further includes determining a normalized signal distance between a first signal measurement corresponding to a first landmark candidate of the plurality of landmark candidates and a second signal measurement corresponding to a second landmark candidate of the plurality of landmark candidates. The method further includes determining, at the computing system, that the first landmark corresponds to the second landmark based on the normalized signal distance.
Abstract:
An apparatus may include a memory to store a first radio signal strength indicator (RSSI) data set comprising first data entries for RSSI detected from a multiplicity of transmission sources by a first wireless device of a first device type, and to store a second RSSI data set comprising second data entries for RSSI detected from the multiplicity of transmission sources by a second wireless device of a second device type; and a cross-device radio calibration engine to receive the first RSSI data set and second RSSI data set and generate a cross-calibrated RSSI function comprising a function that reduces differences between the first RSSI data set and the second RSSI data set. Other embodiments are disclosed and claimed.