Package: ipft 0.7.2

ipft: Indoor Positioning Fingerprinting Toolset

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.

Authors:Emilio Sansano [aut, cre], Raúl Montoliu [ctb]

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ipft.pdf |ipft.html
ipft/json (API)

# Install 'ipft' in R:
install.packages('ipft', repos = c('https://esansano.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • 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).
  • 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).

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

14 exports 0.00 score 34 dependencies 17 scripts 188 downloads

Last updated 7 years agofrom:58752baf78. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 10 2024
R-4.5-win-x86_64OKSep 10 2024
R-4.5-linux-x86_64OKSep 10 2024
R-4.4-win-x86_64OKSep 10 2024
R-4.4-mac-x86_64OKSep 10 2024
R-4.4-mac-aarch64OKSep 10 2024
R-4.3-win-x86_64OKSep 10 2024
R-4.3-mac-x86_64OKSep 10 2024
R-4.3-mac-aarch64OKSep 10 2024

Exports:ipfClusteripfDistanceipfEstimateipfEstimateBeaconPositionsipfGroupipfKnnipfPlotEcdfipfPlotEstimationipfPlotLocationipfPlotPdfipfProbabilisticipfProximityipfRMIDipfTransform

Dependencies:apclustercliclustercolorspacedplyrfansifarvergenericsggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerRcpprlangscalestibbletidyselectutf8vctrsviridisLitewithr

Readme and manuals

Help Manual

Help pageTopics
Creates clusters using the specified methodipfCluster
Distance functionipfDistance
Estimates the location of the test observationsipfEstimate
Estimates the positions of the emitter beaconsipfEstimateBeaconPositions
Creates groups based on the specified parametersipfGroup
Implements the k-nearest neighbors algorithmipfKnn
Plots the cumulative distribution function of the estimated erroripfPlotEcdf
Plots the estimated locationsipfPlotEstimation
Plots the spatial location of the observationsipfPlotLocation
Plots the probability density function of the estimated erroripfPlotPdf
This function implements a probabilistic algorithmipfProbabilistic
Estimates the position of the observations from its fingerprints and the access point location usins a logarithmic path loss modelipfProximity
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).ipfpwap
Estimates the inherent difficulty of the radio mapipfRMID
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).ipftest
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).ipftrain
Transform functionipfTransform