Abstract: A method and system of maintaining a trained neural network for mobile device indoor navigation and positioning. The method comprises, based on magnetic parameters acquired from a plurality of mobile devices acquired at a set of positions within an indoor area, accumulating the magnetic parameters in accordance with a trained neural network-based magnetic fingerprint dataset in a fingerprint database of the indoor area; and when a density of points represented by the set of positions having accumulated magnetic parameters exceeds a deployment threshold density, deploying the magnetic fingerprint dataset within a fingerprint map for mobile device navigation of the indoor area, the fingerprint map encompassing the set of positions.

Abstract: Methods and systems of crowd-sourced magnetic fingerprinting for mobile device indoor navigation with neural network re-training are described. In an example, at multiple locations, magnetic input parameters in accordance with a magnetic infrastructure profile of an indoor area are determined. Further, from a mobile device positioned at a first location, measured magnetic parameters at respective ones of multiple locations are received. A route segment similarity factor for the mobile device based on the measured magnetic parameters of a corresponding route segment accessible from the magnetic fingerprint dataset is computed. If the similarity factor exceeds a threshold, the magnetic measured parameters are added to the magnetic fingerprint dataset. For at least a second location along the route, another set of magnetic measured parameters is received from the mobile device.

Abstract: A method and system of maintaining a trained neural network for mobile device indoor navigation and positioning. The method comprises receiving a set of magnetic measured parameters acquired at a mobile device positioned at a first location of an indoor area; computing, at an output layer of a trained neural network, an output error based on comparing a magnetic input feature in accordance with the magnetic measured parameters to a magnetic output feature generated at the output layer, the magnetic output feature being generated at least in part based on a matrix of weights associated with at least a first neural network layer; and if the output error exceeds a threshold value, re-training the neural network based at least in part upon re-initializing the matrix of weights associated with the at least a first neural network layer.

Abstract: A method and system of crowd-sourced magnetic fingerprinting for mobile device indoor navigation with neural network re-training.

Abstract: A method and system of maintaining a trained neural network for mobile device indoor navigation and positioning. The method comprises receiving a set of magnetic measured parameters acquired at a mobile device positioned at a first location of an indoor area; computing, at an output layer of a trained neural network, an output error based on comparing a magnetic input feature in accordance with the magnetic measured parameters to a magnetic output feature generated at the output layer, the magnetic output feature being generated at least in part based on a matrix of weights associated with at least a first neural network layer; and if the output error exceeds a threshold value, re-training the neural network based at least in part upon re-initializing the matrix of weights associated with the at least a first neural network layer.

Abstract: A method and system of maintaining a trained neural network for mobile device indoor navigation and positioning. The method comprises, based on magnetic parameters acquired from a plurality of mobile devices acquired at a set of positions within an indoor area, accumulating the magnetic parameters in accordance with a trained neural network-based magnetic fingerprint dataset in a fingerprint database of the indoor area; and when a density of points represented by the set of positions having accumulated magnetic parameters exceeds a deployment threshold density, deploying the magnetic fingerprint dataset within a fingerprint map for mobile device navigation of the indoor area, the fingerprint map encompassing the set of positions.

Abstract: A method and system of infrastructure re-purposed magnetic signatures for mobile device indoor navigation and positioning. The method comprises determining a common spatial region in accordance with a first spatial region partially superimposed upon an at least a second spatial region, the first and at least a second spatial regions associated with a first and an at least a second magnetic signatures respectively; and generating, based at least in part on the first and at least a second magnetic signatures, a re-purposed magnetic signature associated with the common spatial region.

Abstract: A method and system of instantiating a recalibration of a magnetic fingerprint dataset of indoor facilities or infrastructure for mobile device navigation. The method comprises, based on magnetic parameters acquired from a plurality of mobile devices acquired at a set of positions within an indoor area, accumulating the magnetic parameters in accordance with a trained neural network-based magnetic fingerprint dataset in a fingerprint database of the indoor area, identifying respective positions of a subset of the set of positions having a variance that exceeds a threshold variance between observed magnetic parameters and magnetic parameters determined in accordance with the trained neural network, and when contiguous positions of the subset are encompassed by a boundary representing a portion of the indoor area, instantiating a re-calibration of the magnetic fingerprint dataset for mobile device navigation within the portion of the indoor area.

Abstract: A method and system of localizing a mobile device having a processor and a memory. The method comprises localizing the mobile device to a first set of positions along a route traversed in the indoor area using a full set of data fusion inputs that includes at least wireless signal data, inertial sensor data, and magnetic field data based on one or more sensor devices of the mobile device, receiving an indication of a magnetic field distortion along the route being traversed, contemporaneous with the localizing to the first set of positions based on the full set of data fusion inputs, localizing the mobile device to a second set of positions along the route based on a subset of the set of data fusion inputs that does not include the magnetic data, and when the first and second sets of positions coincide in accordance with a threshold difference in distance, reverting to localizing the mobile device in accordance with the full set of data fusion inputs.

Abstract: A method and system of localizing a mobile device having a processor and a memory. The method comprises localizing the mobile device to a first set of positions along a route traversed in the indoor area using a full set of data fusion inputs that includes at least wireless signal data, inertial sensor data, and magnetic field data based on one or more sensor devices of the mobile device, receiving an indication of a magnetic field distortion along the route being traversed, contemporaneous with the localizing to the first set of positions based on the full set of data fusion inputs, localizing the mobile device to a second set of positions along the route based on a subset of the set of data fusion inputs that does not include the magnetic data, and when the first and second sets of positions coincide in accordance with a threshold difference in distance, reverting to localizing the mobile device in accordance with the full set of data fusion inputs.

Abstract: A method and system of deploying a trained neural network-based RSS fingerprint dataset for mobile device indoor navigation and positioning. The method comprises: based on RSS parameters acquired from a plurality of mobile devices acquired at a set of positions within an indoor area, accumulating the RSS parameters as a trained neural network-based RSS fingerprint dataset in a fingerprint database of the indoor area; and when a density of points represented by the set of positions having accumulated RSS parameters exceeds a deployment threshold density, deploying the RSS fingerprint dataset within a fingerprint map for mobile device navigation of the indoor area, the fingerprint map encompassing the set of positions.

Abstract: A method and system of crowd-sourced training of a neural network for mobile device indoor navigation and positioning. The method, executed in a processor of a server computing device, comprises: based on RSS parameters acquired at a mobile device from a wireless signal source, localizing the mobile device to a first position within indoor area in accordance with a probabilistic confidence level; if the confidence level exceeds a threshold confidence level, adding the RSS parameters in association with the first position to a fingerprint database of the indoor area; and training a neural network implemented in the processor at least in part based on the RSS parameters as added to the fingerprint database.

Abstract: A method and system of maintaining a trained neural network for mobile device indoor navigation and positioning.

Abstract: A method and system of instantiating a lightweight re-calibration of a received signal strength (RSS) fingerprint dataset for mobile device indoor navigation. The method comprises, based on RSS parameters acquired from a plurality of mobile devices acquired at a set of positions within an indoor area, accumulating the RSS parameters in accordance with a trained neural network-based RSS fingerprint dataset in a fingerprint database of the indoor area; identifying respective positions of a subset of the set of positions having a variance that exceeds a threshold variance between observed RSS parameters and RSS parameters determined in accordance the trained neural network; and when contiguous positions of the subset are encompassed by a boundary representing a portion of the indoor area, instantiating a re-calibration of the RSS fingerprint dataset for mobile device navigation within the portion of the indoor area.

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 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 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: 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: 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: 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.