Indoor Positioning Fingerprinting Toolset
Creates clusters using the specified method
Distance function
Estimates the location of the test observations
Estimates the positions of the emitter beacons
Creates groups based on the specified parameters
Implements the k-nearest neighbors algorithm
Plots the cumulative distribution function of the estimated error
Plots the estimated locations
Plots the spatial location of the observations
Plots the probability density function of the estimated error
This function implements a probabilistic algorithm
Estimates the position of the observations from its fingerprints and t...
Estimates the inherent difficulty of the radio map
Transform function
Algorithms and utility functions for indoor positioning using fingerprinting techniques. These functions are designed for manipulation of RSSI (Received Signal Strength Intensity) data sets, estimation of positions,comparison of the performance of different models, and graphical visualization of data. Machine learning algorithms and methods such as k-nearest neighbors or probabilistic fingerprinting are implemented in this package to perform analysis and estimations over RSSI data sets.