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Dataset . 2025
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Dataset . 2025
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2024
License: CC BY
Data sources: Datacite
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Evaluation of underfloor accelerometers through fingerprinting for indoor localization

Authors: Belli, Dimitri; Crivello, Antonino; La Rosa, Davide; Barsocchi, Paolo;

Evaluation of underfloor accelerometers through fingerprinting for indoor localization

Abstract

Fingerprinting Code developed to test the effectiveness of an indoor positioning system where multiple accelerometers are placed under the floor and set up to collect data. This material complements the work done for the paper "Evaluation of Underfloor Accelerometers for Enabling Location-based Services in Intelligent Environments" and helps readers to reproduce and validate the results presented in that paper. What the code doesThe execution of the main code performs the following:1. generation of sensor maps through their absolute coordinates;2. noise reduction on the raw data according to the average of the stress the accelerometers are subjected at quiet;3. generation of the fingerprint maps per each data set;4. generation of the clean ground truth files (deleting coordinates set to zero);5. computation of the n-dimensional distance between observations at a given time step and the euclidean error between the minimum distance value coordinates and the respective temporally closest ground truth ones;6. same as in 5 but with intra-user fingerprint maps;7. same as in 5 but with inter-user fingerprint maps;8. same as in 5 but with enhanced inter-user fingerprint maps. To run the code please read the file README.md

Keywords

indoor localization, accelerometers, fingerprinting, indoor positioning, intelligent floor

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average