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.

De Sanctis, M., Conte, A., Rossi, T., Di Domenico, S., & Cianca, E. (2021). Cir-based device-free people counting via uwb signals. SENSORS, 21(9) [10.3390/s21093296].

Cir-based device-free people counting via uwb signals

De Sanctis M.;Rossi T.;Di Domenico S.;Cianca E.
2021

Abstract

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.
Pubblicato
Rilevanza internazionale
Articolo
Esperti anonimi
Settore ING-INF/03
eng
Channel impulse response
People counting
RF sensing
UWB
Communicable Disease Control
Humans
Masks
SARS-CoV-2
COVID-19
Hand Hygiene
De Sanctis, M., Conte, A., Rossi, T., Di Domenico, S., & Cianca, E. (2021). Cir-based device-free people counting via uwb signals. SENSORS, 21(9) [10.3390/s21093296].
De Sanctis, M; Conte, A; Rossi, T; Di Domenico, S; Cianca, E
Articolo su rivista
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2108/290880
Citazioni
  • ???jsp.display-item.citation.pmc??? 1
  • Scopus 1
  • ???jsp.display-item.citation.isi??? 1
social impact