Abstract: The present subject matter relates to a computing device (104) and method intended to provide fine-grained continuous location tracking for non-real time uses (e.g., for retracing the movement of office employees). As per the subject matter, the knowledge of an office layout is combined with the application of particle filters (PFs) over inertial tracking (using compass, accelerometer and gyroscope sensors) data. Viterbi-based path-likelihood maximization is integrated with PF framework to progressively reduce the uncertainty in the movement track of an individual computing device (104).

Abstract: Disclosed is a method and Geographic Information System (GIS) for creating a user's proximity model in accordance with a user's feedback. The GIS creates the user's proximity model using a Dempster-Shafer technique. The GIS initializes the user's proximity model upon initializing a fuzzy set with a fuzzy membership function. The fuzzy set includes a plurality of points scattered around a reference point. The GIS creates an intermediate model using the user's proximity model by selecting a group of points from the plurality of points. The GIS receives a user feedback on the intermediate model. The GIS adapts the fuzzy membership function based on the user feedback. The GIS then updates the user's proximity model based on the fuzzy membership function which is adapted on basis of the user feedback.

Abstract: The present subject matter relates to a computing device (104) and method intended to provide fine-grained continuous location tracking for non-real time uses (e.g., for retracing the movement of office employees). As per the subject matter, the knowledge of an office layout is combined with the application of particle filters (PFs) over inertial tracking (using compass, accelerometer and gyroscope sensors) data. Viterbi-based path-likelihood maximization is integrated with PF framework to progressively reduce the uncertainty in the movement track of an individual computing device (104).

Abstract: Disclosed is a method and Geographic Information System (GIS) for creating a user's proximity model in accordance with a user's feedback. The GIS creates the user's proximity model using a Dempster-Shafer technique. The GIS initializes the user's proximity model upon initializing a fuzzy set with a fuzzy membership function. The fuzzy set includes a plurality of points scattered around a reference point. The GIS creates an intermediate model using the user's proximity model by selecting a group of points from the plurality of points. The GIS receives a user feedback on the intermediate model. The GIS adapts the fuzzy membership function based on the user feedback. The GIS then updates the user's proximity model based on the fuzzy membership function which is adapted on basis of the user feedback.