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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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 AT aleandroconte cirbaseddevicefreepeoplecountingviauwbsignals AT tommasorossi cirbaseddevicefreepeoplecountingviauwbsignals AT simonedidomenico cirbaseddevicefreepeoplecountingviauwbsignals AT ernestinacianca cirbaseddevicefreepeoplecountingviauwbsignals |
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