CIR-Based Device-Free People Counting via UWB Signals

The outbreak of COVID-19 has resulted in many different policies being adopted across the world to reduce the spread of the virus. These policies include wearing surgical masks, hand hygiene practices, increased social distancing and full country-wide lockdown. Specifically, social distancing involv...

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Main Authors: Mauro De Sanctis, Aleandro Conte, Tommaso Rossi, Simone Di Domenico, Ernestina Cianca
Format: Article
Language:English
Published: MDPI AG 2021-05-01
Series:Sensors
Subjects:
UWB
Online Access:https://www.mdpi.com/1424-8220/21/9/3296
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spelling doaj-12eb9061dd584a5f8d7de4488eda9c2f2021-05-31T23:36:54ZengMDPI AGSensors1424-82202021-05-01213296329610.3390/s21093296CIR-Based Device-Free People Counting via UWB SignalsMauro De Sanctis0Aleandro Conte1Tommaso Rossi2Simone Di Domenico3Ernestina Cianca4Department of Electronics Engineering, University of Rome “Tor Vergata”, 00133 Roma, ItalyDepartment of Electronics Engineering, University of Rome “Tor Vergata”, 00133 Roma, ItalyDepartment of Electronics Engineering, University of Rome “Tor Vergata”, 00133 Roma, ItalyDepartment of Electronics Engineering, University of Rome “Tor Vergata”, 00133 Roma, ItalyDepartment of Electronics Engineering, University of Rome “Tor Vergata”, 00133 Roma, ItalyThe outbreak of COVID-19 has resulted in many different policies being adopted across the world to reduce the spread of the virus. These policies include wearing surgical masks, hand hygiene practices, increased social distancing and full country-wide lockdown. Specifically, social distancing involves keeping a certain distance from others and avoiding gathering together in large groups. Automatic crowd density estimation is a technological solution that could help in guaranteeing social distancing by reducing the probability that two persons in a public area come in close proximity to each other while moving around. This paper proposes a novel low complexity RF sensing system for automatic people counting based on low cost UWB transceivers. The proposed system is based on an ordinary classifier that exploits features extracted from the channel impulse response of UWB communication signals. Specifically, features are extracted from the sorted list of singular values obtained from the singular value decomposition applied to the matrix of the channel impulse response vector differences. Experimental results achieved in two different environments show that the proposed system is a promising candidate for future automatic crowd density monitoring systems.https://www.mdpi.com/1424-8220/21/9/3296RF sensingUWBpeople countingchannel impulse response
collection DOAJ
language English
format Article
sources DOAJ
author Mauro De Sanctis
Aleandro Conte
Tommaso Rossi
Simone Di Domenico
Ernestina Cianca
spellingShingle Mauro De Sanctis
Aleandro Conte
Tommaso Rossi
Simone Di Domenico
Ernestina Cianca
CIR-Based Device-Free People Counting via UWB Signals
Sensors
RF sensing
UWB
people counting
channel impulse response
author_facet Mauro De Sanctis
Aleandro Conte
Tommaso Rossi
Simone Di Domenico
Ernestina Cianca
author_sort Mauro De Sanctis
title CIR-Based Device-Free People Counting via UWB Signals
title_short CIR-Based Device-Free People Counting via UWB Signals
title_full CIR-Based Device-Free People Counting via UWB Signals
title_fullStr CIR-Based Device-Free People Counting via UWB Signals
title_full_unstemmed CIR-Based Device-Free People Counting via UWB Signals
title_sort cir-based device-free people counting via uwb signals
publisher MDPI AG
series Sensors
issn 1424-8220
publishDate 2021-05-01
description The outbreak of COVID-19 has resulted in many different policies being adopted across the world to reduce the spread of the virus. These policies include wearing surgical masks, hand hygiene practices, increased social distancing and full country-wide lockdown. Specifically, social distancing involves keeping a certain distance from others and avoiding gathering together in large groups. Automatic crowd density estimation is a technological solution that could help in guaranteeing social distancing by reducing the probability that two persons in a public area come in close proximity to each other while moving around. This paper proposes a novel low complexity RF sensing system for automatic people counting based on low cost UWB transceivers. The proposed system is based on an ordinary classifier that exploits features extracted from the channel impulse response of UWB communication signals. Specifically, features are extracted from the sorted list of singular values obtained from the singular value decomposition applied to the matrix of the channel impulse response vector differences. Experimental results achieved in two different environments show that the proposed system is a promising candidate for future automatic crowd density monitoring systems.
topic RF sensing
UWB
people counting
channel impulse response
url https://www.mdpi.com/1424-8220/21/9/3296
work_keys_str_mv AT maurodesanctis cirbaseddevicefreepeoplecountingviauwbsignals
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AT simonedidomenico cirbaseddevicefreepeoplecountingviauwbsignals
AT ernestinacianca cirbaseddevicefreepeoplecountingviauwbsignals
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