Indoor air quality monitoring system for proactive control of respiratory infectious diseases: Poster abstract

Yao Hua Ho; Pei En Li; Ling Jyh Chen; Yu Lun Liu

doi:10.1145/3384419.3430456

Indoor air quality monitoring system for proactive control of respiratory infectious diseases: Poster abstract

Yao Hua Ho, Pei En Li, Ling Jyh Chen, Yu Lun Liu

Department of Computer Science and Information Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Disease surveillance is essential for the control of flu and respiratory infectious diseases including the novel coronavirus disease (COVID-19). Indoor air quality monitoring has been shown effective in understanding the effectiveness of airflow and circulation indoors to reduce the risk of infectious diseases. In this project, we developed low-cost indoor air quality monitoring devices and systems to tackle the disease surveillance problem. The monitoring device consists of a set of air quality sensors. By strategic deployment and real-time data analysis, the system is able to yield insightful air circulation information indoors. The real-time data analysis is performed on air quality for the indoor ventilation using Long Short-Term Memory (LSTM) on sensed data. A series of user-friendly visualization interfaces and chatbot applications are designed to interact with users and ensure the successful delivery of infection control information. Finally, we work closely with the Taiwan Centers for Disease Control (CDC) and conduct field experiments in 15 locations including hospitals, long-term care centers, schools with total of 144 IAQ devices.

Original language	English
Title of host publication	SenSys 2020 - Proceedings of the 2020 18th ACM Conference on Embedded Networked Sensor Systems
Publisher	Association for Computing Machinery, Inc
Pages	693-694
Number of pages	2
ISBN (Electronic)	9781450375900
DOIs	https://doi.org/10.1145/3384419.3430456
Publication status	Published - 2020 Nov 16
Event	18th ACM Conference on Embedded Networked Sensor Systems, SenSys 2020 - Virtual, Online, Japan Duration: 2020 Nov 16 → 2020 Nov 19

Publication series

Name	SenSys 2020 - Proceedings of the 2020 18th ACM Conference on Embedded Networked Sensor Systems

Conference

Conference	18th ACM Conference on Embedded Networked Sensor Systems, SenSys 2020
Country	Japan
City	Virtual, Online
Period	2020/11/16 → 2020/11/19

Keywords

indoor air quality
internet of thing
respiratory disease

ASJC Scopus subject areas

Control and Systems Engineering
Electrical and Electronic Engineering
Computer Networks and Communications

UN SDGs

This output contributes to the following Sustainable Development Goal(s)

Access to Document

10.1145/3384419.3430456

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Ho, Y. H., Li, P. E., Chen, L. J., & Liu, Y. L. (2020). Indoor air quality monitoring system for proactive control of respiratory infectious diseases: Poster abstract. In SenSys 2020 - Proceedings of the 2020 18th ACM Conference on Embedded Networked Sensor Systems (pp. 693-694). (SenSys 2020 - Proceedings of the 2020 18th ACM Conference on Embedded Networked Sensor Systems). Association for Computing Machinery, Inc. https://doi.org/10.1145/3384419.3430456

Indoor air quality monitoring system for proactive control of respiratory infectious diseases : Poster abstract. / Ho, Yao Hua; Li, Pei En; Chen, Ling Jyh; Liu, Yu Lun.

SenSys 2020 - Proceedings of the 2020 18th ACM Conference on Embedded Networked Sensor Systems. Association for Computing Machinery, Inc, 2020. p. 693-694 (SenSys 2020 - Proceedings of the 2020 18th ACM Conference on Embedded Networked Sensor Systems).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Ho, YH, Li, PE, Chen, LJ & Liu, YL 2020, Indoor air quality monitoring system for proactive control of respiratory infectious diseases: Poster abstract. in SenSys 2020 - Proceedings of the 2020 18th ACM Conference on Embedded Networked Sensor Systems. SenSys 2020 - Proceedings of the 2020 18th ACM Conference on Embedded Networked Sensor Systems, Association for Computing Machinery, Inc, pp. 693-694, 18th ACM Conference on Embedded Networked Sensor Systems, SenSys 2020, Virtual, Online, Japan, 2020/11/16. https://doi.org/10.1145/3384419.3430456

Ho YH, Li PE, Chen LJ, Liu YL. Indoor air quality monitoring system for proactive control of respiratory infectious diseases: Poster abstract. In SenSys 2020 - Proceedings of the 2020 18th ACM Conference on Embedded Networked Sensor Systems. Association for Computing Machinery, Inc. 2020. p. 693-694. (SenSys 2020 - Proceedings of the 2020 18th ACM Conference on Embedded Networked Sensor Systems). https://doi.org/10.1145/3384419.3430456

Ho, Yao Hua ; Li, Pei En ; Chen, Ling Jyh ; Liu, Yu Lun. / Indoor air quality monitoring system for proactive control of respiratory infectious diseases : Poster abstract. SenSys 2020 - Proceedings of the 2020 18th ACM Conference on Embedded Networked Sensor Systems. Association for Computing Machinery, Inc, 2020. pp. 693-694 (SenSys 2020 - Proceedings of the 2020 18th ACM Conference on Embedded Networked Sensor Systems).

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title = "Indoor air quality monitoring system for proactive control of respiratory infectious diseases: Poster abstract",

abstract = "Disease surveillance is essential for the control of flu and respiratory infectious diseases including the novel coronavirus disease (COVID-19). Indoor air quality monitoring has been shown effective in understanding the effectiveness of airflow and circulation indoors to reduce the risk of infectious diseases. In this project, we developed low-cost indoor air quality monitoring devices and systems to tackle the disease surveillance problem. The monitoring device consists of a set of air quality sensors. By strategic deployment and real-time data analysis, the system is able to yield insightful air circulation information indoors. The real-time data analysis is performed on air quality for the indoor ventilation using Long Short-Term Memory (LSTM) on sensed data. A series of user-friendly visualization interfaces and chatbot applications are designed to interact with users and ensure the successful delivery of infection control information. Finally, we work closely with the Taiwan Centers for Disease Control (CDC) and conduct field experiments in 15 locations including hospitals, long-term care centers, schools with total of 144 IAQ devices.",

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author = "Ho, {Yao Hua} and Li, {Pei En} and Chen, {Ling Jyh} and Liu, {Yu Lun}",

note = "Funding Information: We present an Indoor Air Quality Monitoring System for Proactive Control of Respiratory Infectious Diseases. The system consists of Data Producers (i.e., IAQ devices), Data Broker (i.e., backend server), and Data Consumers (i.e., data analysis application, visualization interfaces, and chatbot applications). Working closely with Taiwan CDC, a real-world experiments is conducted with 15 locations with 144 IAQ devices including hospitals, long-term care centers, and schools. Based on the evaluation results and feedbacks received throughout this study, we evaluate the feasibility of the proposed system for disease surveillance, as well as make a concrete plan for large-scale deployment in the future. Acknowledgments. This project is supported by the Taiwan Centers for Disease Control (CDC) Technology Research Project [Grant number: MOHW109-CDC-C-114-123601]. Publisher Copyright: {\textcopyright} 2020 ACM. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; 18th ACM Conference on Embedded Networked Sensor Systems, SenSys 2020 ; Conference date: 16-11-2020 Through 19-11-2020",

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AU - Liu, Yu Lun

N1 - Funding Information: We present an Indoor Air Quality Monitoring System for Proactive Control of Respiratory Infectious Diseases. The system consists of Data Producers (i.e., IAQ devices), Data Broker (i.e., backend server), and Data Consumers (i.e., data analysis application, visualization interfaces, and chatbot applications). Working closely with Taiwan CDC, a real-world experiments is conducted with 15 locations with 144 IAQ devices including hospitals, long-term care centers, and schools. Based on the evaluation results and feedbacks received throughout this study, we evaluate the feasibility of the proposed system for disease surveillance, as well as make a concrete plan for large-scale deployment in the future. Acknowledgments. This project is supported by the Taiwan Centers for Disease Control (CDC) Technology Research Project [Grant number: MOHW109-CDC-C-114-123601]. Publisher Copyright: © 2020 ACM. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.

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N2 - Disease surveillance is essential for the control of flu and respiratory infectious diseases including the novel coronavirus disease (COVID-19). Indoor air quality monitoring has been shown effective in understanding the effectiveness of airflow and circulation indoors to reduce the risk of infectious diseases. In this project, we developed low-cost indoor air quality monitoring devices and systems to tackle the disease surveillance problem. The monitoring device consists of a set of air quality sensors. By strategic deployment and real-time data analysis, the system is able to yield insightful air circulation information indoors. The real-time data analysis is performed on air quality for the indoor ventilation using Long Short-Term Memory (LSTM) on sensed data. A series of user-friendly visualization interfaces and chatbot applications are designed to interact with users and ensure the successful delivery of infection control information. Finally, we work closely with the Taiwan Centers for Disease Control (CDC) and conduct field experiments in 15 locations including hospitals, long-term care centers, schools with total of 144 IAQ devices.

AB - Disease surveillance is essential for the control of flu and respiratory infectious diseases including the novel coronavirus disease (COVID-19). Indoor air quality monitoring has been shown effective in understanding the effectiveness of airflow and circulation indoors to reduce the risk of infectious diseases. In this project, we developed low-cost indoor air quality monitoring devices and systems to tackle the disease surveillance problem. The monitoring device consists of a set of air quality sensors. By strategic deployment and real-time data analysis, the system is able to yield insightful air circulation information indoors. The real-time data analysis is performed on air quality for the indoor ventilation using Long Short-Term Memory (LSTM) on sensed data. A series of user-friendly visualization interfaces and chatbot applications are designed to interact with users and ensure the successful delivery of infection control information. Finally, we work closely with the Taiwan Centers for Disease Control (CDC) and conduct field experiments in 15 locations including hospitals, long-term care centers, schools with total of 144 IAQ devices.

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Indoor air quality monitoring system for proactive control of respiratory infectious diseases: Poster abstract

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

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