TY - JOUR
T1 - An empirical study of the transmission power setting for bluetooth-based indoor localization mechanisms
AU - Castillo-Cara, Manuel
AU - Lovón-Melgarejo, Jesús
AU - Bravo-Rocca, Gusseppe
AU - Orozco-Barbosa, Luis
AU - García-Varea, Ismael
N1 - Publisher Copyright:
© 2017 by the authors. Licensee MDPI, Basel, Switzerland.
Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2017/6/7
Y1 - 2017/6/7
N2 - 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.
AB - 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.
KW - Ble4.0
KW - Bluetooth
KW - Indoor positioning
KW - Location fingerprinting
KW - Multipath fading
KW - Rssi
KW - Signal processing
KW - Supervised learning algorithm
KW - Transmission power
UR - http://www.scopus.com/inward/record.url?scp=85020470076&partnerID=8YFLogxK
U2 - 10.3390/s17061318
DO - 10.3390/s17061318
M3 - Artículo (Contribución a Revista)
C2 - 28590413
AN - SCOPUS:85020470076
SN - 1424-8220
VL - 17
JO - Sensors (Switzerland)
JF - Sensors (Switzerland)
IS - 6
M1 - 1318
ER -