Cargando…

An Improved Method Based on Bluetooth Low-Energy Fingerprinting for the Implementation of PEPS System

In the automotive field, the introduction of keyless access systems is revolutionizing car entry techniques currently dominated by a physical key. In this context, this paper investigates the possible use of smartphones to create a PEPS (Passive Entry Passive Start) system using the BLE (Bluetooth L...

Descripción completa

Detalles Bibliográficos
Autores principales: Bonavolontà, Francesco, Liccardo, Annalisa, Schiano Lo Moriello, Rosario, Caputo, Enzo, de Alteriis, Giorgio, Palladino, Angelo, Vitolo, Giuseppe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9783498/
https://www.ncbi.nlm.nih.gov/pubmed/36559982
http://dx.doi.org/10.3390/s22249615
_version_ 1784857591388569600
author Bonavolontà, Francesco
Liccardo, Annalisa
Schiano Lo Moriello, Rosario
Caputo, Enzo
de Alteriis, Giorgio
Palladino, Angelo
Vitolo, Giuseppe
author_facet Bonavolontà, Francesco
Liccardo, Annalisa
Schiano Lo Moriello, Rosario
Caputo, Enzo
de Alteriis, Giorgio
Palladino, Angelo
Vitolo, Giuseppe
author_sort Bonavolontà, Francesco
collection PubMed
description In the automotive field, the introduction of keyless access systems is revolutionizing car entry techniques currently dominated by a physical key. In this context, this paper investigates the possible use of smartphones to create a PEPS (Passive Entry Passive Start) system using the BLE (Bluetooth Low-Energy) Fingerprinting technique that allows, along with a connection to a low-cost BLE micro-controllers network, determining the driver’s position, either inside or outside the vehicle. Several issues have been taken into account to assure the reliability of the proposal; in particular, (i) spatial orientation of each microcontroller-based BLE node which ensures the best performance at 180° and 90° referred to as the BLE scanner and the advertiser, respectively; (ii) data filtering techniques based on Kalman Filter; and (iii) definition of new network topology, resulting from the merger of two standard network topologies. Particular attention has been paid to the selection of the appropriate measurement method capable of assuring the most reliable positioning results by means of the adoption of only six embedded BLE devices. This way, the global accuracy of the system reaches 98.5%, while minimum and maximum accuracy values relative to the individual zones equal, respectively, to 97.3% and 99.4% have been observed, thus confirming the capability of the proposed method of recognizing whether the driver is inside or outside the vehicle.
format Online
Article
Text
id pubmed-9783498
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-97834982022-12-24 An Improved Method Based on Bluetooth Low-Energy Fingerprinting for the Implementation of PEPS System Bonavolontà, Francesco Liccardo, Annalisa Schiano Lo Moriello, Rosario Caputo, Enzo de Alteriis, Giorgio Palladino, Angelo Vitolo, Giuseppe Sensors (Basel) Article In the automotive field, the introduction of keyless access systems is revolutionizing car entry techniques currently dominated by a physical key. In this context, this paper investigates the possible use of smartphones to create a PEPS (Passive Entry Passive Start) system using the BLE (Bluetooth Low-Energy) Fingerprinting technique that allows, along with a connection to a low-cost BLE micro-controllers network, determining the driver’s position, either inside or outside the vehicle. Several issues have been taken into account to assure the reliability of the proposal; in particular, (i) spatial orientation of each microcontroller-based BLE node which ensures the best performance at 180° and 90° referred to as the BLE scanner and the advertiser, respectively; (ii) data filtering techniques based on Kalman Filter; and (iii) definition of new network topology, resulting from the merger of two standard network topologies. Particular attention has been paid to the selection of the appropriate measurement method capable of assuring the most reliable positioning results by means of the adoption of only six embedded BLE devices. This way, the global accuracy of the system reaches 98.5%, while minimum and maximum accuracy values relative to the individual zones equal, respectively, to 97.3% and 99.4% have been observed, thus confirming the capability of the proposed method of recognizing whether the driver is inside or outside the vehicle. MDPI 2022-12-08 /pmc/articles/PMC9783498/ /pubmed/36559982 http://dx.doi.org/10.3390/s22249615 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Bonavolontà, Francesco
Liccardo, Annalisa
Schiano Lo Moriello, Rosario
Caputo, Enzo
de Alteriis, Giorgio
Palladino, Angelo
Vitolo, Giuseppe
An Improved Method Based on Bluetooth Low-Energy Fingerprinting for the Implementation of PEPS System
title An Improved Method Based on Bluetooth Low-Energy Fingerprinting for the Implementation of PEPS System
title_full An Improved Method Based on Bluetooth Low-Energy Fingerprinting for the Implementation of PEPS System
title_fullStr An Improved Method Based on Bluetooth Low-Energy Fingerprinting for the Implementation of PEPS System
title_full_unstemmed An Improved Method Based on Bluetooth Low-Energy Fingerprinting for the Implementation of PEPS System
title_short An Improved Method Based on Bluetooth Low-Energy Fingerprinting for the Implementation of PEPS System
title_sort improved method based on bluetooth low-energy fingerprinting for the implementation of peps system
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9783498/
https://www.ncbi.nlm.nih.gov/pubmed/36559982
http://dx.doi.org/10.3390/s22249615
work_keys_str_mv AT bonavolontafrancesco animprovedmethodbasedonbluetoothlowenergyfingerprintingfortheimplementationofpepssystem
AT liccardoannalisa animprovedmethodbasedonbluetoothlowenergyfingerprintingfortheimplementationofpepssystem
AT schianolomoriellorosario animprovedmethodbasedonbluetoothlowenergyfingerprintingfortheimplementationofpepssystem
AT caputoenzo animprovedmethodbasedonbluetoothlowenergyfingerprintingfortheimplementationofpepssystem
AT dealteriisgiorgio animprovedmethodbasedonbluetoothlowenergyfingerprintingfortheimplementationofpepssystem
AT palladinoangelo animprovedmethodbasedonbluetoothlowenergyfingerprintingfortheimplementationofpepssystem
AT vitologiuseppe animprovedmethodbasedonbluetoothlowenergyfingerprintingfortheimplementationofpepssystem
AT bonavolontafrancesco improvedmethodbasedonbluetoothlowenergyfingerprintingfortheimplementationofpepssystem
AT liccardoannalisa improvedmethodbasedonbluetoothlowenergyfingerprintingfortheimplementationofpepssystem
AT schianolomoriellorosario improvedmethodbasedonbluetoothlowenergyfingerprintingfortheimplementationofpepssystem
AT caputoenzo improvedmethodbasedonbluetoothlowenergyfingerprintingfortheimplementationofpepssystem
AT dealteriisgiorgio improvedmethodbasedonbluetoothlowenergyfingerprintingfortheimplementationofpepssystem
AT palladinoangelo improvedmethodbasedonbluetoothlowenergyfingerprintingfortheimplementationofpepssystem
AT vitologiuseppe improvedmethodbasedonbluetoothlowenergyfingerprintingfortheimplementationofpepssystem