Visualizing Effects of COVID-19 Social Isolation with Residential Activity Big Data Sensor Data

Anuradha Rajkumar; Bruce Wallace; Laura Ault; Julien Lariviere-Chartier; Frank Knoefel; Rafik Goubran; Jeff Kaye; Neil Thomas

doi:10.1109/BigData50022.2020.9377830

Visualizing Effects of COVID-19 Social Isolation with Residential Activity Big Data Sensor Data

Anuradha Rajkumar, Bruce Wallace, Laura Ault, Julien Lariviere-Chartier, Frank Knoefel, Rafik Goubran, Jeff Kaye, Neil Thomas

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

2 Scopus citations

Abstract

The ability to understand and visualize big data sets is of increasing interest to caregivers and clinicians as ambient home sensing can provide massive amounts of data related to the activities of residents. However, this data is only useful if it can be effectively and simply visualized for review and analysis. This paper presents the visualization of longitudinal data sets from ambient well-being sensors deployed in 3 residences that have a spousal pair dyad where 1 resident has been diagnosed with Mild Cognitive Impairment or Dementia and the spousal partner is acting as a caregiver. The paper presents the differences in activity and behaviour that can be observed in the 3 residences by comparing two 30-day periods prior to and one 30-day period during COVID-19 social isolation precautions. The work shows the potential for this circle plot based visualization technique to summarize resident activity and also to convey external factors such as the variation in solar day that can itself influence behaviour.

Original language	English (US)
Title of host publication	Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020
Editors	Xintao Wu, Chris Jermaine, Li Xiong, Xiaohua Tony Hu, Olivera Kotevska, Siyuan Lu, Weijia Xu, Srinivas Aluru, Chengxiang Zhai, Eyhab Al-Masri, Zhiyuan Chen, Jeff Saltz
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	3811-3819
Number of pages	9
ISBN (Electronic)	9781728162515
DOIs	https://doi.org/10.1109/BigData50022.2020.9377830
State	Published - Dec 10 2020
Externally published	Yes
Event	8th IEEE International Conference on Big Data, Big Data 2020 - Virtual, Atlanta, United States Duration: Dec 10 2020 → Dec 13 2020

Publication series

Name	Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020

Conference

Conference	8th IEEE International Conference on Big Data, Big Data 2020
Country/Territory	United States
City	Virtual, Atlanta
Period	12/10/20 → 12/13/20

Keywords

IoT
ambient sensing
big data visualization
cloud processing
smart home technology

ASJC Scopus subject areas

Computer Networks and Communications
Information Systems
Information Systems and Management
Safety, Risk, Reliability and Quality

Access to Document

10.1109/BigData50022.2020.9377830

Cite this

Rajkumar, A., Wallace, B., Ault, L., Lariviere-Chartier, J., Knoefel, F., Goubran, R., Kaye, J., & Thomas, N. (2020). Visualizing Effects of COVID-19 Social Isolation with Residential Activity Big Data Sensor Data. In X. Wu, C. Jermaine, L. Xiong, X. T. Hu, O. Kotevska, S. Lu, W. Xu, S. Aluru, C. Zhai, E. Al-Masri, Z. Chen, & J. Saltz (Eds.), Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020 (pp. 3811-3819). Article 9377830 (Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BigData50022.2020.9377830

Visualizing Effects of COVID-19 Social Isolation with Residential Activity Big Data Sensor Data. / Rajkumar, Anuradha; Wallace, Bruce; Ault, Laura et al.
Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020. ed. / Xintao Wu; Chris Jermaine; Li Xiong; Xiaohua Tony Hu; Olivera Kotevska; Siyuan Lu; Weijia Xu; Srinivas Aluru; Chengxiang Zhai; Eyhab Al-Masri; Zhiyuan Chen; Jeff Saltz. Institute of Electrical and Electronics Engineers Inc., 2020. p. 3811-3819 9377830 (Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020).

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

Rajkumar, A, Wallace, B, Ault, L, Lariviere-Chartier, J, Knoefel, F, Goubran, R, Kaye, J & Thomas, N 2020, Visualizing Effects of COVID-19 Social Isolation with Residential Activity Big Data Sensor Data. in X Wu, C Jermaine, L Xiong, XT Hu, O Kotevska, S Lu, W Xu, S Aluru, C Zhai, E Al-Masri, Z Chen & J Saltz (eds), Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020., 9377830, Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020, Institute of Electrical and Electronics Engineers Inc., pp. 3811-3819, 8th IEEE International Conference on Big Data, Big Data 2020, Virtual, Atlanta, United States, 12/10/20. https://doi.org/10.1109/BigData50022.2020.9377830

Rajkumar A, Wallace B, Ault L, Lariviere-Chartier J, Knoefel F, Goubran R et al. Visualizing Effects of COVID-19 Social Isolation with Residential Activity Big Data Sensor Data. In Wu X, Jermaine C, Xiong L, Hu XT, Kotevska O, Lu S, Xu W, Aluru S, Zhai C, Al-Masri E, Chen Z, Saltz J, editors, Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020. Institute of Electrical and Electronics Engineers Inc. 2020. p. 3811-3819. 9377830. (Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020). doi: 10.1109/BigData50022.2020.9377830

Rajkumar, Anuradha ; Wallace, Bruce ; Ault, Laura et al. / Visualizing Effects of COVID-19 Social Isolation with Residential Activity Big Data Sensor Data. Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020. editor / Xintao Wu ; Chris Jermaine ; Li Xiong ; Xiaohua Tony Hu ; Olivera Kotevska ; Siyuan Lu ; Weijia Xu ; Srinivas Aluru ; Chengxiang Zhai ; Eyhab Al-Masri ; Zhiyuan Chen ; Jeff Saltz. Institute of Electrical and Electronics Engineers Inc., 2020. pp. 3811-3819 (Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020).

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abstract = "The ability to understand and visualize big data sets is of increasing interest to caregivers and clinicians as ambient home sensing can provide massive amounts of data related to the activities of residents. However, this data is only useful if it can be effectively and simply visualized for review and analysis. This paper presents the visualization of longitudinal data sets from ambient well-being sensors deployed in 3 residences that have a spousal pair dyad where 1 resident has been diagnosed with Mild Cognitive Impairment or Dementia and the spousal partner is acting as a caregiver. The paper presents the differences in activity and behaviour that can be observed in the 3 residences by comparing two 30-day periods prior to and one 30-day period during COVID-19 social isolation precautions. The work shows the potential for this circle plot based visualization technique to summarize resident activity and also to convey external factors such as the variation in solar day that can itself influence behaviour.",

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note = "Funding Information: This work was supported in part by the AGE-WELL NCE Inc and National Innovation hub programs (Platform Project Program, AW-PP2019-PP5), a Bruy{\`e}re Research Institute New Investigator Grant, in part by the National Institute on Aging (NIA) grants: P30 AG008017; P30 AG066518; P30 AG024978; U2CAG0543701 and by the Natural Sciences and Engineering Research Council (NSERC) Discovery Grant. Publisher Copyright: {\textcopyright} 2020 IEEE.; 8th IEEE International Conference on Big Data, Big Data 2020 ; Conference date: 10-12-2020 Through 13-12-2020",

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Visualizing Effects of COVID-19 Social Isolation with Residential Activity Big Data Sensor Data

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this