A Novel Privacy-Preserving Approach for Physical Distancing Measurement Using Thermal Sensor Array

Abdallah Naser; Ahmad Lotfi; Joni Zhong

doi:10.1145/3453892.3453903

A Novel Privacy-Preserving Approach for Physical Distancing Measurement Using Thermal Sensor Array

Abdallah Naser
, Ahmad Lotfi
, Joni Zhong

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

12 Citations (Scopus)

Abstract

Physical distancing measurements are accepted to be critical strategies to slow the spread of COVID-19 disease. Most of the recent works to measure the physical distancing between people aims for easy-to-deploy systems such as contact tracing applications to speed up the deployment process. However, these systems, which rely heavily on the Bluetooth proximity sensor, tend to have serious performance and reliability issues. This paper proposes and explores using Thermal Sensor Array (TSA) towards physical distancing measurement. Distance estimation is achieved through using a multilayer perceptron (MLP) artificial neural network to measure the sensor-to-human distance and then to compute the physical distancing accordingly. Based on the conducted experimental work, the proposed sensor-to-human distance estimator's median overall error is ± 0.2m for unseen testing data.

Original language	English
Title of host publication	14th ACM International Conference on PErvasive Technologies Related to Assistive Environments, PETRA 2021
Publisher	Association for Computing Machinery
Pages	81-85
Number of pages	5
ISBN (Electronic)	9781450387927
DOIs	https://doi.org/10.1145/3453892.3453903
Publication status	Published - 29 Jun 2021
Event	14th ACM International Conference on PErvasive Technologies Related to Assistive Environments, PETRA 2021 - Virtual, Online, Greece Duration: 29 Jun 2021 → 1 Jul 2021

Publication series

Name	ACM International Conference Proceeding Series

Conference

Conference	14th ACM International Conference on PErvasive Technologies Related to Assistive Environments, PETRA 2021
Country/Territory	Greece
City	Virtual, Online
Period	29/06/21 → 1/07/21

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

adaptive system
artificial neural network
distance estimation
human-centred approach
Physical distancing
semantic segmentation
thermal sensor array

ASJC Scopus subject areas

Software
Human-Computer Interaction
Computer Vision and Pattern Recognition
Computer Networks and Communications

More information

10.1145/3453892.3453903

Cite this

Naser, A., Lotfi, A., & Zhong, J. (2021). A Novel Privacy-Preserving Approach for Physical Distancing Measurement Using Thermal Sensor Array. In 14th ACM International Conference on PErvasive Technologies Related to Assistive Environments, PETRA 2021 (pp. 81-85). (ACM International Conference Proceeding Series). Association for Computing Machinery. https://doi.org/10.1145/3453892.3453903

@inproceedings{6c2ee94e3e38411998ddce38e15c5e06,

title = "A Novel Privacy-Preserving Approach for Physical Distancing Measurement Using Thermal Sensor Array",

abstract = "Physical distancing measurements are accepted to be critical strategies to slow the spread of COVID-19 disease. Most of the recent works to measure the physical distancing between people aims for easy-to-deploy systems such as contact tracing applications to speed up the deployment process. However, these systems, which rely heavily on the Bluetooth proximity sensor, tend to have serious performance and reliability issues. This paper proposes and explores using Thermal Sensor Array (TSA) towards physical distancing measurement. Distance estimation is achieved through using a multilayer perceptron (MLP) artificial neural network to measure the sensor-to-human distance and then to compute the physical distancing accordingly. Based on the conducted experimental work, the proposed sensor-to-human distance estimator's median overall error is ± 0.2m for unseen testing data.",

keywords = "adaptive system, artificial neural network, distance estimation, human-centred approach, Physical distancing, semantic segmentation, thermal sensor array",

author = "Abdallah Naser and Ahmad Lotfi and Joni Zhong",

note = "Publisher Copyright: {\textcopyright} 2021 ACM.; 14th ACM International Conference on PErvasive Technologies Related to Assistive Environments, PETRA 2021 ; Conference date: 29-06-2021 Through 01-07-2021",

year = "2021",

month = jun,

day = "29",

doi = "10.1145/3453892.3453903",

language = "English",

series = "ACM International Conference Proceeding Series",

publisher = "Association for Computing Machinery",

pages = "81--85",

booktitle = "14th ACM International Conference on PErvasive Technologies Related to Assistive Environments, PETRA 2021",

}

Naser, A, Lotfi, A & Zhong, J 2021, A Novel Privacy-Preserving Approach for Physical Distancing Measurement Using Thermal Sensor Array. in 14th ACM International Conference on PErvasive Technologies Related to Assistive Environments, PETRA 2021. ACM International Conference Proceeding Series, Association for Computing Machinery, pp. 81-85, 14th ACM International Conference on PErvasive Technologies Related to Assistive Environments, PETRA 2021, Virtual, Online, Greece, 29/06/21. https://doi.org/10.1145/3453892.3453903

A Novel Privacy-Preserving Approach for Physical Distancing Measurement Using Thermal Sensor Array. / Naser, Abdallah; Lotfi, Ahmad; Zhong, Joni.
14th ACM International Conference on PErvasive Technologies Related to Assistive Environments, PETRA 2021. Association for Computing Machinery, 2021. p. 81-85 (ACM International Conference Proceeding Series).

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

TY - GEN

T1 - A Novel Privacy-Preserving Approach for Physical Distancing Measurement Using Thermal Sensor Array

AU - Naser, Abdallah

AU - Lotfi, Ahmad

AU - Zhong, Joni

PY - 2021/6/29

Y1 - 2021/6/29

N2 - Physical distancing measurements are accepted to be critical strategies to slow the spread of COVID-19 disease. Most of the recent works to measure the physical distancing between people aims for easy-to-deploy systems such as contact tracing applications to speed up the deployment process. However, these systems, which rely heavily on the Bluetooth proximity sensor, tend to have serious performance and reliability issues. This paper proposes and explores using Thermal Sensor Array (TSA) towards physical distancing measurement. Distance estimation is achieved through using a multilayer perceptron (MLP) artificial neural network to measure the sensor-to-human distance and then to compute the physical distancing accordingly. Based on the conducted experimental work, the proposed sensor-to-human distance estimator's median overall error is ± 0.2m for unseen testing data.

AB - Physical distancing measurements are accepted to be critical strategies to slow the spread of COVID-19 disease. Most of the recent works to measure the physical distancing between people aims for easy-to-deploy systems such as contact tracing applications to speed up the deployment process. However, these systems, which rely heavily on the Bluetooth proximity sensor, tend to have serious performance and reliability issues. This paper proposes and explores using Thermal Sensor Array (TSA) towards physical distancing measurement. Distance estimation is achieved through using a multilayer perceptron (MLP) artificial neural network to measure the sensor-to-human distance and then to compute the physical distancing accordingly. Based on the conducted experimental work, the proposed sensor-to-human distance estimator's median overall error is ± 0.2m for unseen testing data.

KW - adaptive system

KW - artificial neural network

KW - distance estimation

KW - human-centred approach

KW - Physical distancing

KW - semantic segmentation

KW - thermal sensor array

UR - https://www.scopus.com/pages/publications/85109252642

U2 - 10.1145/3453892.3453903

DO - 10.1145/3453892.3453903

M3 - Conference article published in proceeding or book

AN - SCOPUS:85109252642

T3 - ACM International Conference Proceeding Series

SP - 81

EP - 85

BT - 14th ACM International Conference on PErvasive Technologies Related to Assistive Environments, PETRA 2021

PB - Association for Computing Machinery

T2 - 14th ACM International Conference on PErvasive Technologies Related to Assistive Environments, PETRA 2021

Y2 - 29 June 2021 through 1 July 2021

ER -

A Novel Privacy-Preserving Approach for Physical Distancing Measurement Using Thermal Sensor Array

Abstract

Publication series

Conference

UN SDGs

Keywords

ASJC Scopus subject areas

More information

Other files and links

Fingerprint

Cite this