TY - GEN
T1 - Supporting Home Quarantine with Smart Speakers
AU - Alrumayh, Abrar S.
AU - Tan, Chiu C.
N1 - Publisher Copyright:
© 2020 ACM.
PY - 2020/6/19
Y1 - 2020/6/19
N2 - The outbreak of COVID-19 has been lead many countries to ask their citizens to home quarantine. Smart speakers, like the Google Home or Amazon Alexa, that continuously listen for voice commands, can potentially be used to help in monitoring adherence to quarantine rules. This paper proposes a monitoring solution to count the number of occupants in a home. Our technique is sufficiently lightweight to avoid using backend cloud computing facility so as to protect privacy, and is robust against common background noises such as television. To evaluate the performance of our technique, we perform experiments on real-world traces recorded from five different families. Our results show that the proposed algorithm is able to count the family member reliably across different home environments.
AB - The outbreak of COVID-19 has been lead many countries to ask their citizens to home quarantine. Smart speakers, like the Google Home or Amazon Alexa, that continuously listen for voice commands, can potentially be used to help in monitoring adherence to quarantine rules. This paper proposes a monitoring solution to count the number of occupants in a home. Our technique is sufficiently lightweight to avoid using backend cloud computing facility so as to protect privacy, and is robust against common background noises such as television. To evaluate the performance of our technique, we perform experiments on real-world traces recorded from five different families. Our results show that the proposed algorithm is able to count the family member reliably across different home environments.
KW - COVID-19
KW - Home Quarantine
KW - Smart Speakers
UR - https://www.scopus.com/pages/publications/85088124530
UR - https://www.scopus.com/pages/publications/85088124530#tab=citedBy
U2 - 10.1145/3396868.3400897
DO - 10.1145/3396868.3400897
M3 - Conference contribution
AN - SCOPUS:85088124530
T3 - HealthDL 2020 - Proceedings of the 2020 Deep Learning for Wellbeing Applications Leveraging Mobile Devices and Edge Computing
SP - 3
EP - 8
BT - HealthDL 2020 - Proceedings of the 2020 Deep Learning for Wellbeing Applications Leveraging Mobile Devices and Edge Computing
T2 - 2020 Deep Learning for Wellbeing Applications Leveraging Mobile Devices and Edge Computing, HealthDL 2020
Y2 - 19 June 2020
ER -