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ipft (version 0.7.2)

Indoor Positioning Fingerprinting Toolset

Description

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.

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Version

Install

install.packages('ipft')

Monthly Downloads

185

Version

0.7.2

License

GPL (>= 2)

Maintainer

Emilio Sansano

Last Published

January 4th, 2018

Functions in ipft (0.7.2)

ipfProbabilistic

This function implements a probabilistic algorithm
ipfProximity

Estimates the position of the observations from its fingerprints and the access point location usins a logarithmic path loss model
ipfCluster

Creates clusters using the specified method
ipfDistance

Distance function
ipfPlotLocation

Plots the spatial location of the observations
ipfPlotPdf

Plots the probability density function of the estimated error
ipfPlotEcdf

Plots the cumulative distribution function of the estimated error
ipfPlotEstimation

Plots the estimated locations
ipfpwap

Indoor localization data set with the positions of the wireless access points present in the ipftrain and ipftest data sets. Unknown locations are stored as NAs. Data from the positioning tutorial of the seventh international conference on indoor Positioning and Indoor Navigation (IPIN2016).
ipftest

Indoor localization test data set to test Indoor Positioning System that rely on WLAN/WiFifingerprint. It was created during the Fingerprinting-based Indoor Positioning tutorial of the seventh international conference on indoor Positioning and Indoor Navigation (IPIN2016).
ipfGroup

Creates groups based on the specified parameters
ipfKnn

Implements the k-nearest neighbors algorithm
ipftrain

Indoor localization training data set to test Indoor Positioning System that rely on WLAN/WiFifingerprint. It was created during the Fingerprinting-based Indoor Positioning tutorial of the seventh international conference on indoor Positioning and Indoor Navigation (IPIN2016).
ipfEstimate

Estimates the location of the test observations
ipfEstimateBeaconPositions

Estimates the positions of the emitter beacons
ipfRMID

Estimates the inherent difficulty of the radio map
ipfTransform

Transform function