Published March 10, 2022 | Version v1.0.0
Dataset Open

Bluetooth indoor localization Dataset

Creators

  • 1. Universidad Nacional de Educación a Distancia

Description

Bluetooth indoor localization Dataset: Collected to perform experimentation on how bluetooth signal strengths can be used to determine one of the indoor locations. The dataset has 6 transmission power, from Tx01 to Tx06; and in each dataset have 5 features with the bluetooth RSSI because the enviroment have 5 BLE4.0 and 1 categorical target that is the sector where the person is located (15 sectors total).

Files

Data_BLE_indoor_Localization.zip

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Additional details

Identifiers

DOI
10.1109/ACCESS.2019.2899736
DOI
10.1109/LA-CCI.2017.8285716

Related works

Is supplement to
Journal article: 10.1016/j.inffus.2022.10.011 (DOI)
Is supplemented by
Journal article: 10.3390/s17061318 (DOI)
Journal article: 10.1109/ACCESS.2019.2899736 (DOI)

Dates

Accepted
2023

Software

Repository URL
https://github.com/manwestc/Localization-Symm_Asymm/tree/v0.1.1
Programming language
Python
Development Status
Active

References

  • Lovón-Melgarejo, J., Castillo-Cara, M., Huarcaya-Canal, O., Orozco-Barbosa, L., & Garcia-Varea, I. (2019). Comparative study of supervised learning and metaheuristic algorithms for the development of bluetooth-based indoor localization mechanisms. IEEE Access, 7, 26123-26135.
  • Castillo-Cara, M., Lovón-Melgarejo, J., Bravo-Rocca, G., Orozco-Barbosa, L., & García-Varea, I. (2017). An empirical study of the transmission power setting for bluetooth-based indoor localization mechanisms. Sensors, 17(6), 1318.
  • Lovon-Melgarejo, J., Castillo-Cara, M., Orozco-Barbosa, L., & García-Varea, I. (2017, November). Supervised learning algorithms for indoor localization fingerprinting using BLE4. 0 beacons. In 2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI) (pp. 1-6). IEEE.