Abstract: A method and a system for recommending a pedestrian route based on crowd-sourced pedestrian navigation associated with an indoor area. The method comprises displaying a set of graphical icons representing a respective route traversal profile option, the set rendered within a graphical user interface (GUI) of a mobile device, the GUI depicting a layout of the indoor area, receiving a selection of a graphical icon from the set, storing route activity data in association with the selected graphical icon during traversal, by the mobile device, of a route within the layout, adding the route activity data to accumulated route navigation data associated with the selected graphical icon, and based on a predetermined threshold associated with the adding, deploying the respective route traversal profile option represented by the selected graphical icon, the profile option recommending the pedestrian route based at least in part on the route activity data.

Abstract: A method and system for facilitating an access request. The method may be executed in the processor of a server computing device and comprises receiving, at a memory of the server computing device, the request for access, the request for access performed using a security device at an access point device communicatively coupled to the server computing device, localizing a mobile computing device having a preestablished association with the security device, and enabling the request for access when a position of the mobile computing device as determined from the localizing is within a predetermined threshold distance from a location of the access point device.

Abstract: Methods and Systems of adjusting a radio frequency (RF) broadcast signal power level in a crowd-sourced mobile device localization system in a pedestrian area are described. In an example, a first mobile device and a second mobile device may be localized to establish a first estimated position a second estimated position, respectively. The localizing may be based on fingerprint data of the pedestrian area, wherein a localization data packet including the first estimated position broadcasted by the first mobile device at a first broadcast power level and another localization data packet including the second estimated position broadcasted by the second broadcast device at a second broadcast power level may be received.

Abstract: A method and system of adjusting a radio frequency (RF) broadcast signal power level in a crowd-sourced mobile device localization system in a pedestrian area.

Abstract: A method and system for deploying a calibrated positioning map of an area. The method, executed in a processor of a server computing device, comprises generating, using the processor, a distribution of positioning data points based at least in part on a first set of fingerprint data, the positioning data points calibrated in accordance with respective positions within the area, receiving, at the memory, a second set of fingerprint data, processing, using the processor, the second set of fingerprint data and the positioning data points to generate an updated distribution of positioning data points, and when the updated distribution exceeds a threshold density of positioning data points, deploying the updated distribution as the positioning map of the area.

Abstract: A method and system for detecting an indoor threshold transition in a positioning state. The method may be executable using one or more processors and comprises, upon detecting a pattern of magnetic anomaly characteristics associated with a sequence of position changes of the mobile device, extracting the pattern, comparing the extracted pattern with a stored magnetic signature associated with the indoor threshold, and based on the comparing, inferring that the mobile device is one of transitioning in position and has transitioned in position across the indoor threshold.

Abstract: Embodiments of the present disclosure related to methods and systems of determining the position of a device.

Abstract: A method and a system of providing, for display at a mobile computing device, a pedestrian route associated with an indoor facility. The method comprises localizing the mobile computing device at a first position of the indoor facility, determining a credential associated with the mobile computing device, and communicating, for display at the mobile computing device, the pedestrian route from the first position to at least a second position of the indoor facility, the pedestrian route determined at least partly based on the credential.

Abstract: A method and system localizing a mobile device along a pedestrian route traversed in an indoor area, the mobile device including a processor and a memory.

Abstract: A method and a system for recommending a pedestrian route based on crowd-sourced pedestrian navigation associated with an indoor area. The method comprises displaying a set of graphical icons representing a respective route traversal profile option, the set rendered within a graphical user interface (GUI) of a mobile device, the GUI depicting a layout of the indoor area, receiving a selection of a graphical icon from the set, storing route activity data in association with the selected graphical icon during traversal, by the mobile device, of a route within the layout, adding the route activity data to accumulated route navigation data associated with the selected graphical icon, and based on a predetermined threshold associated with the adding, deploying the respective route traversal profile option represented by the selected graphical icon, the profile option recommending the pedestrian route based at least in part on the route activity data.

Abstract: A method and system of broadcasting crowd-sourced localization data from a mobile device within a pedestrian area. The method, executed in the processor of the mobile device, comprises localizing the mobile device by determining an estimated position of the mobile device within the pedestrian area based on accessing fingerprint data of the pedestrian area, broadcasting, at a first broadcast power level, a localization data packet that includes data of the estimated position to one or more peer mobile devices within the pedestrian area, determining a confidence level indicative of a degree of accuracy for the estimated position, and continuing the broadcasting at one of a lower and a higher broadcast power level than the first broadcast power level when it is determined that the confidence level is one of above and below a threshold confidence level.

Abstract: Embodiments of the present disclosure related to methods and systems of determining the position of a device.

Abstract: A method and system for deploying a calibrated positioning map of an area. The method, executed in a processor of a server computing device, comprises receiving, at a memory of the server computing device, a first set of fingerprint data acquired within the area by a plurality of mobile devices, generating, using the processor, a distribution of calibrated data points based at least in part on the first set of fingerprint data, the calibrated data points representing respective positions within the area, receiving, at the memory, a second set of fingerprint data acquired by at least one additional mobile device, processing, using the processor, the second set of fingerprint data and the calibrated data points to generate an updated distribution of calibrated data points, and when the updated distribution exceeds a predetermined threshold density of calibration data points, deploying the updated distribution as the calibrated positioning map of the area.

Abstract: Embodiments of the present disclosure related to methods and systems of determining the floor and location of a device in an indoor space having multiple floors. A map importing module takes a floor map of an indoor space and processes it for further use. A calibration module creates a fingerprint map of the indoor space described by the floor map. A floor localization module searches the fingerprint map of each floor to determine the most likely location for each floor. A floor detection module determines the floor and location based on the most likely locations for each floor and any of map constraints data and device movement data.

Abstract: A method and system for deploying a calibrated positioning map of an area. The method, executed in a processor of a server computing device, comprises receiving, at a memory of the server computing device, a first set of fingerprint data acquired within the area by a plurality of mobile devices, generating, using the processor, a distribution of calibrated data points based at least in part on the first set of fingerprint data, the calibrated data points representing respective positions within the area, receiving, at the memory, a second set of fingerprint data acquired by at least one additional mobile device, processing, using the processor, the second set of fingerprint data and the calibrated data points to generate an updated distribution of calibrated data points, and when the updated distribution exceeds a predetermined threshold density of calibration data points, deploying the updated distribution as the calibrated positioning map of the area.

Abstract: Embodiments of the present disclosure relate to methods and systems of updating an orientation of a mobile device in a global reference frame. The method includes gathering mobile device gyroscope data, gathering mobile device accelerometer data, gathering mobile device magnetometer data, determining a first orientation of the mobile device based on the gyroscope data, determining a second orientation of the mobile device based on the device accelerometer data and the device magnetometer data, determining a trust factor associated with the second orientation, and updating the orientation of the mobile device based on the first orientation, the second orientation, and the trust factor.

Abstract: Embodiments of the present disclosure related to methods and systems of determining the position of a device in indoor space. A map importing module takes a floor map of an indoor space and processes it for further use. A calibration module creates a fingerprint map of the indoor space described by the floor map. A positioning module uses the calibration data embodied in a fingerprint map as well as device signal and sensor readings in order to estimate a trajectory for the device, then position the device within the indoor space described by the floor map using a probability density function.

Abstract: Embodiments of the present disclosure related to methods and systems of determining the floor and location of a device in an indoor space having multiple floors. A map importing module takes a floor map of an indoor space and processes it for further use. A calibration module creates a fingerprint map of the indoor space described by the floor map. A floor localization module searches the fingerprint map of each floor to determine the most likely location for each floor. A floor detection module determines the floor and location by comparing the most likely locations for each floor and utilizing device movement history data.

Abstract: Embodiments of the present disclosure related to methods and systems of determining the position of a device in indoor space. A map importing module takes a floor map of an indoor space and processes it for further use. A calibration module creates a fingerprint map of the indoor space described by the floor map. A positioning module uses the calibration data embodied in a fingerprint map as well as device signal and sensor readings in order to estimate a trajectory for the device, then position the device within the indoor space described by the floor map using a probability density function.

Abstract: Embodiments of the present disclosure related to methods and systems of determining the floor and location of a device in an indoor space having multiple floors. A map importing module takes a floor map of an indoor space and processes it for further use. A calibration module creates a fingerprint map of the indoor space described by the floor map. A floor localization module searches the fingerprint map of each floor to determine the most likely location for each floor. A floor detection module determines the floor and location by comparing the most likely locations for each floor and utilizing device movement history data.