Abstract:
A location of a wireless device relative to a vehicle is determined using received data. Data may be received from the vehicle sensors. Data may also be received from the wireless device sensors of a wireless device. The presence of one or more persons may be determined using received data. A user-to-wireless device association may be detected based, at least in part, upon the presence of one or more persons in the vehicle and the location of the wireless device relative to the vehicle.
Abstract:
The disclosure relates to automatic calibration for cross devices in Wi-Fi fingerprint based areas. In an exemplary embodiment, an online device scans and obtains multiple signal strength value (RSSI o i ) from local access points. The online device may access a fingerprint database and obtain a set of fingerprints. Each fingerprint includes a known location, a set of RSSI values (RSSI f i ) and optionally a device/model name. For each fingerprint, the online device: (1) calculates a fingerprint RSSI offset (fpOff) in real-time; (2) applies the fingerprint RSSI offset (fpOff) to the fingerprint RSSI values to determine adjusted fingerprint values. Then the online device identifies fingerprints with minimum Euclidean distance and uses their RSSI offset (fpOff) value to determine a device RSSI offset value. The device offset value can be used to calibrate the online device and to provide accurate location information.
Abstract:
Various embodiments are generally directed to techniques to merge a virtual map derived from sensors of computing devices moved about an interior of a structure with a corresponding physical map. An apparatus to merge maps includes a processor component; and a merged map generator for execution by the processor component to merge a virtual map and a physical map to generate a merged map, the virtual map comprising indications of virtual pathways through an interior of a structure based on sensors, and the physical map comprising indications of physical pathways of the interior. Other embodiments are described and claimed.
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:
This document discloses one or more systems, apparatuses, methods, etc. for detecting precise indoor location of a portable wireless device based on a WiFi simultaneous localization and mapping (SLAM) algorithm that implements spatial and temporal coherence. In an implementation, a SLAM algorithm includes WiFi similarities and inertial navigational system (INS) measurements data as location estimates (i.e., references) for the spatial and temporal coherences implementations to constitute the WiFi SLAM algorithm.
Abstract:
Embodiments herein relate to determining the location of a device using hybrid localization techniques. For example, a first technique such as trilateration may be used to determine an approximate location of the device. An error associated with the approximate location may also be implemented to increase the likelihood of locating the device upon applying a second localization technique, such as fingerprinting. Fingerprinting, when applied to the approximate location determined from trilateration, may determine the location of the device, or a more precise location than that determined from trilateration, such that reduced power consumption by the device may be achieved without sacrificing location accuracy.
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:
The present disclosure relates to computer-implemented systems and methods for location estimation using a mobile device. An example method may include receiving, at a device, one or more signature measurements associated with an indoor environment. Additionally, the device may be associated with a user. The method may also include receiving, at the device, one or more motion tracking measurements to measure relative motion associated with the device and the user. Furthermore, the method may include associating the one or more signature measurements with one or more virtual landmarks identified within the indoor environment. The method may further include determining a location of the user based on the one or more signature measurements, the one or more motion tracking measurements, and the one or more virtual landmarks.
Abstract:
Certain embodiments herein are directed to reducing variations in received signal strength indicator (RSSI) measurements that may be received by a wireless device over a network, such as a WiFi network including one or more access points. A signal sent from an access point may be received by a user device, where channel estimation results associated with the received signal may be analyzed to determine a more accurate location of the user device. The received signal may be converted to at least one of the time domain and the frequency domain, in which signal components associated with the received signal may be identified based on a determination that the signal components may be associated with multipath fading or other types of interference. Such identified signal components, whether in the frequency domain or the time domain) may be excluded from a determination of a signal strength measurement that may in turn be used to identify the location of the user device.
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.