An empirical study of the transmission power setting for bluetooth-based indoor localization mechanisms

Manuel Castillo-Cara, Jesús Lovón-Melgarejo, Gusseppe Bravo-Rocca, Luis Orozco-Barbosa, Ismael García-Varea

Research output: Contribution to journalArticle (Contribution to Journal)peer-review

30 Scopus citations

Abstract

Nowadays, there is a great interest in developing accurate wireless indoor localization mechanisms enabling the implementation of many consumer-oriented services. Among the many proposals, wireless indoor localization mechanisms based on the Received Signal Strength Indication (RSSI) are being widely explored. Most studies have focused on the evaluation of the capabilities of different mobile device brands and wireless network technologies. Furthermore, different parameters and algorithms have been proposed as a means of improving the accuracy of wireless-based localization mechanisms. In this paper,we focus on the tuning of the RSSI fingerprint to be used in the implementation of a Bluetooth Low Energy 4.0 (BLE4.0) Bluetooth localization mechanism. Following a holistic approach, we start by assessing the capabilities of two Bluetooth sensor/receiver devices. We then evaluate the relevance of the RSSI fingerprint reported by each BLE4.0 beacon operating at various transmission power levels using feature selection techniques. Based on our findings, we use two classification algorithms in order to improve the setting of the transmission power levels of each of the BLE4.0 beacons. Our main findings show that our proposal can greatly improve the localization accuracy by setting a custom transmission power level for each BLE4.0 beacon.

Original languageEnglish
Article number1318
JournalSensors (Switzerland)
Volume17
Issue number6
DOIs
StatePublished - 7 Jun 2017
Externally publishedYes

Keywords

  • Ble4.0
  • Bluetooth
  • Indoor positioning
  • Location fingerprinting
  • Multipath fading
  • Rssi
  • Signal processing
  • Supervised learning algorithm
  • Transmission power

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