Abstract: A method and a device for determining motion of a device are described. In an example, a plurality of points-of-interest (POIs) are identified in a pedestrian area of an indoor space and, with each POI, a probabilistic representation of motion transition of a device from the POI is associated. The probabilistic representation of motion transition is indicative of a probability distribution of likely directions of motion that the device can exhibit from the POI. Further, a map of the indoor space is generated based on the association and the map is usable for ascertaining motion of the device in the indoor space.

Abstract: A method and a system of maintaining data connectivity between a mobile device during traversal of a pedestrian facility and a server computing device via a set of intermediary communication devices.

Abstract: Examples of generating a map for an indoor space are described. In one example, a raw digital representation of the indoor space is obtained and preprocessed by at least one of marking a region-of-interest (ROI) in the raw digital representation and classifying the indoor space into a space-category to obtain a preprocessed representation. Using the preprocessed representation, a skeletal map is generated including indicators to identify elements of the indoor space. Revision inputs are received to modify an erroneous indicator from amongst the multiple indicators. The erroneous indicator is revised to a modified indicator and the modified indicator and unmodified indicators are used to create a modified skeletal map which is usable for localizing a mobile device in the indoor space.

Abstract: A method and a device for criterion-based calibration for localization of mobile devices are described. In an example, sensorial data for a zone in the indoor space is obtained. The zone can have a set of factors influencing a behavior of the sensorial data therein. A component of instantaneous localization in the zone is determined based on the sensorial data by simulating variation of the component. The estimation is evaluated based on a ground truth value of the component and, on the basis thereof, a localization criterion is associated with the zone. The localization criterion is indicative of a selectivity in use of the sensorial data for localizing the mobile device in the zone.

Abstract: A method and a device for performing automated calibration are described. In an example, sensorial data gathered for a space to be mapped in an indoor area is obtained from one or more data recording devices. From the sensorial data, a plurality of trajectories are derived which indicate movement of the one or more data recording devices in the space. Based on the plurality of trajectories, a structural map representing a plurality of map constraints of the space is created. Further, from the sensorial data, calibration information associated with a series of locations in the space is extracted and used along with the structural map to generate a fingerprint map of the space.

Abstract: A method and a device for performing targeted calibration are described. In an example, instructions to acquire spatial data in a predefined region in an indoor space is are received, the indoor space divided into a grid of a plurality of polygonal tiles in a size-wise hierarchy and tessellated at each level of the size-wise hierarchy, wherein the instructions comprise information regarding a group of polygonal tiles from amongst the plurality of polygonal tiles in the predefined region to gather the spatial data for, the group of polygonal tiles selected at a hierarchical level in the size-wise hierarchy, and wherein the spatial data is to be gathered for the group of polygonal tiles along a substantially continuous path connecting the group of polygonal tiles to be traversed for gathering the spatial data. In response to the instructions, acquisition of the spatial data along the substantially continuous path may be commenced.

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 deploying a crowd sourced magnetic fingerprint map for mobile device localization during traversal of the indoor area, accumulating received signal strength (RSS) measurements in forming a RSS fingerprint map using crowd sourced RSS measurements during the deploying, and switching, responsive to identifying desirability of a change in the mobile device localization within the indoor area, from the crowd sourced magnetic fingerprint map to the RSS fingerprint map as basis for localizing the mobile device.

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 magnetic fingerprint based neural network training for mobile device indoor navigation and positioning.

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 magnetic fingerprinting for mobile device indoor navigation and positioning. The method, executed in a processor of a server computing device, comprises generating a magnetic infrastructure profile of at least a portion of the indoor area; determining, in the processor, a magnetic field profile based on the magnetic infrastructure profile; and generating an association of magnetic field profile parameters associated with respective locations within the indoor area as the magnetic fingerprint map.

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 a device for performing targeted calibration are described. In an example, a first set of spatial data acquired within a predefined region in an indoor space is received. The indoor space is represented as a grid of tessellated polygonal tiles arranged in a hierarchical structure of size-wise arranged polygonal tiles. a preliminary discretized spatial map of the calibrated spatial data in the predefined region is generated by linking the first set of spatial data and the corresponding polygonal tiles for which the spatial data has been acquired. From the preliminary discretized spatial map, a group of polygonal tiles are identified which have density of calibrated spatial data less than a threshold density. For the identified polygonal tiles, a second set of spatial data may be acquired. Based on the preliminary discretized spatial map and the second set of spatial data, a fingerprint map is generated for the indoor space.

Abstract: A method and a device for performing targeted calibration are described. In an example, instructions to acquire spatial data in a predefined region in an indoor space is are received, the indoor space divided into a grid of a plurality of polygonal tiles in a size-wise hierarchy and tessellated at each level of the size-wise hierarchy, wherein the instructions comprise information regarding a group of polygonal tiles from amongst the plurality of polygonal tiles in the predefined region to gather the spatial data for, the group of polygonal tiles selected at a hierarchical level in the size-wise hierarchy, and wherein the spatial data is to be gathered for the group of polygonal tiles along a substantially continuous path connecting the group of polygonal tiles to be traversed for gathering the spatial data. In response to the instructions, acquisition of the spatial data along the substantially continuous path may be commenced.

Abstract: A method and a device for localization using grid-based localization of map constraints are described. In an example, an indoor space is divided into a grid of tessellated polygonal tiles in a hierarchical structure. The grid is correlated with physical entities in the indoor space by associating each physical entity with a polygonal tile. Further, an absolute probability value indicative of presence of a device therein is associated with each polygonal tile. As part of associating, the absolute probability value is allocated to each polygonal tile in each hierarchical level to create a probability map for the indoor space. The probability map is used to generate a grid map for the indoor space and the grid map is usable to determine location of the device in the indoor space.

Abstract: Examples for localization using tessellated grids are described. In an example, a plurality of physical entities can be identified in an indoor space and each physical entity can be georeferenced to a coordinate system. The indoor space can be divided into a grid of polygonal tiles abutting adjacent polygonal tiles, and arranged in a hierarchical structure with the tiles in one level of the hierarchical structure being substantially representable by polygonal tiles in other levels of the hierarchical structure. The grid is then spatially indexed by associating each physical entity with a polygonal tile from amongst the polygonal tiles in each hierarchical level, thereby correlating a georeference of the physical entity with the polygonal tile. Based on the spatial indexing, a grid map for the indoor space can be generated for localizing mobile devices in the indoor space.

Abstract: A method and a device for performing targeted calibration are described. In an example, a first set of spatial data acquired within a predefined region in an indoor space is received. The indoor space is represented as a grid of tessellated polygonal tiles arranged in a hierarchical structure of size-wise arranged polygonal tiles. a preliminary discretized spatial map of the calibrated spatial data in the predefined region is generated by linking the first set of spatial data and the corresponding polygonal tiles for which the spatial data has been acquired. From the preliminary discretized spatial map, a group of polygonal tiles are identified which have density of calibrated spatial data less than a threshold density. For the identified polygonal tiles, a second set of spatial data may be acquired. Based on the preliminary discretized spatial map and the second set of spatial data, a fingerprint map is generated for the indoor space.

Abstract: A method and a device for zone-based localization of mobile devices are described. In an example, a zone from amongst a plurality of zones of an indoor space in which a mobile device is present is identified. The identification of the can be based on instantaneous localization information obtained from the mobile device. Further, a localization criterion to be employed for localizing the mobile device is determined based on the identified zone. The localization criterion may be indicative of a selectivity in use of sensor data for localizing the mobile device. Subsequently, the mobile device is localized in the indoor space, based on the localization criterion.

Abstract: A method and system of magnetic parameter based mobile device localization. The method comprises obtaining a predetermined number of magnetic parameter measurements corresponding to a plurality of path segments in an indoor path traversed by a mobile device. Based on accessing a reference database associated with the indoor path, a set of reference segments having a magnetic parameter measurement matching a first magnetic parameter measurement may be identified. In accordance with the identified set of reference segments, a set of alternative trajectories of the mobile device are identified. From the set of alternative trajectories, a current alternative trajectory of the mobile device with a maximum match to the first magnetic parameter measurement may be determined.

Abstract: A method and a system of maintaining data connectivity between a mobile device during traversal of a pedestrian facility and a server computing device via a set of intermediary communication devices.