A way to determine the floor level and location coordinates of a mobile device in a multi-floor indoor space, using fingerprint calibration maps, device sensor data, and device movement data.
A scalable method of determining the indoor location of a device, such as a smartphone, using signal and sensor data points from multiple sensors without relying on hardware installation at the indoor location.
A way to automatically detect the change in location of a mobile device, for example, from indoors to outdoors, based on GPS data and ambient data, including RSS data and/or signal connectivity data.
A way to recommend indoor routes based on crowd-sourced pedestrian navigation data, using a set of icons to represent various route profile options, on a mobile device.
The ability to find the location of a mobile device, using the magnetic signature pattern that represents absolute magnetic field measurements for a sequence of positions along the route that device is being carried.
A crowd-sourced approach to the fingerprint calibration mapping process that enables rapid deployment and easier scalability of an indoor navigation solution.
A method for detecting when a mobile device crosses an entryway indoors, using magnetic signatures associated with magnetic landmarks, for example RFID security devices in mall store doorways.
A method for displaying an indoor route on a mobile device using a predetermined credential associated with the mobile device.
A way to automatically update a self-learning data repository for finding the location of a mobile device, using spatial derivative magnetic fingerprints.
A method of adjusting the radio frequency (RF) signal power levels of mobile devices in an indoor area to control signal interference, in order to enhance the quality of device localization.
A method of finding a mobile device first by using data from multiple sensors of the mobile device, and then, once a set processing time is exceeded, using a portion of that data.
A method of finding a mobile device, while it is being used to navigate along an indoor route, using boundaries identified as a trusted GPS area.
A way to update stored crowd-sourced map data using barometric pressure readings from a mobile device along an indoor route corresponding to the stored map.
A way of training a specific set of algorithms (neural networks) for use in smartphone-based indoor navigation, using RSS features and machine learning.