Literature DB >> 36247189

Internet of Things (IoT) Adoption Model for Early Identification and Monitoring of COVID-19 Cases: A Systematic Review.

Mostafa Shanbehzadeh1, Raoof Nopour2, Hadi Kazemi-Arpanahi3,4.   

Abstract

Background: The 2019 coronavirus disease (COVID-19) is a mysterious and highly infectious disease that was declared a pandemic by the World Health Organization. The virus poses a great threat to global health and the economy. Currently, in the absence of effective treatment or vaccine, leveraging advanced digital technologies is of great importance. In this respect, the Internet of Things (IoT) is useful for smart monitoring and tracing of COVID-19. Therefore, in this study, we have reviewed the literature available on the IoT-enabled solutions to tackle the current COVID-19 outbreak.
Methods: This systematic literature review was conducted using an electronic search of articles in the PubMed, Google Scholar, ProQuest, Scopus, Science Direct, and Web of Science databases to formulate a complete view of the IoT-enabled solutions to monitoring and tracing of COVID-19 according to the FITT (Fit between Individual, Task, and Technology) model.
Results: In the literature review, 28 articles were identified as eligible for analysis. This review provides an overview of technological adoption of IoT in COVID-19 to identify significant users, either primary or secondary, required technologies including technical platform, exchange, processing, storage and added-value technologies, and system tasks or applications at "on-body," "in-clinic/hospital," and even "in-community" levels. Conclusions: The use of IoT along with advanced intelligence and computing technologies for ubiquitous monitoring and tracking of patients in quarantine has made it a critical aspect in fighting the spread of the current COVID-19 and even future pandemics. Copyright:
© 2022 International Journal of Preventive Medicine.

Entities:  

Keywords:  COVID-19; Coronavirus; Internet of Things; systematic review

Year:  2022        PMID: 36247189      PMCID: PMC9564228          DOI: 10.4103/ijpvm.IJPVM_667_20

Source DB:  PubMed          Journal:  Int J Prev Med        ISSN: 2008-7802


  35 in total

1.  Telemedicine and the COVID-19 Pandemic, Lessons for the Future.

Authors:  Rashid Bashshur; Charles R Doarn; Julio M Frenk; Joseph C Kvedar; James O Woolliscroft
Journal:  Telemed J E Health       Date:  2020-04-08       Impact factor: 3.536

2.  Risk-Aware Identification of Highly Suspected COVID-19 Cases in Social IoT: A Joint Graph Theory and Reinforcement Learning Approach.

Authors:  Bowen Wang; Yanjing Sun; Trung Q Duong; Long D Nguyen; Lajos Hanzo
Journal:  IEEE Access       Date:  2020-06-19       Impact factor: 3.367

3.  Visualisation of epidemiological map using an Internet of Things infectious disease surveillance platform.

Authors:  Guanghao Sun; Nguyen Vu Trung; Le Thi Hoi; Pham Thanh Hiep; Koichiro Ishibashi; Takemi Matsui
Journal:  Crit Care       Date:  2020-07-09       Impact factor: 9.097

Review 4.  Internet of things (IoT) applications to fight against COVID-19 pandemic.

Authors:  Ravi Pratap Singh; Mohd Javaid; Abid Haleem; Rajiv Suman
Journal:  Diabetes Metab Syndr       Date:  2020-05-05

5.  Combining Point-of-Care Diagnostics and Internet of Medical Things (IoMT) to Combat the COVID-19 Pandemic.

Authors:  Ting Yang; Mattia Gentile; Ching-Fen Shen; Chao-Min Cheng
Journal:  Diagnostics (Basel)       Date:  2020-04-16

6.  Clinical Characteristics of Coronavirus Disease 2019 in China.

Authors:  Wei-Jie Guan; Zheng-Yi Ni; Yu Hu; Wen-Hua Liang; Chun-Quan Ou; Jian-Xing He; Lei Liu; Hong Shan; Chun-Liang Lei; David S C Hui; Bin Du; Lan-Juan Li; Guang Zeng; Kwok-Yung Yuen; Ru-Chong Chen; Chun-Li Tang; Tao Wang; Ping-Yan Chen; Jie Xiang; Shi-Yue Li; Jin-Lin Wang; Zi-Jing Liang; Yi-Xiang Peng; Li Wei; Yong Liu; Ya-Hua Hu; Peng Peng; Jian-Ming Wang; Ji-Yang Liu; Zhong Chen; Gang Li; Zhi-Jian Zheng; Shao-Qin Qiu; Jie Luo; Chang-Jiang Ye; Shao-Yong Zhu; Nan-Shan Zhong
Journal:  N Engl J Med       Date:  2020-02-28       Impact factor: 91.245

7.  Radiological findings from 81 patients with COVID-19 pneumonia in Wuhan, China: a descriptive study.

Authors:  Heshui Shi; Xiaoyu Han; Nanchuan Jiang; Yukun Cao; Osamah Alwalid; Jin Gu; Yanqing Fan; Chuansheng Zheng
Journal:  Lancet Infect Dis       Date:  2020-02-24       Impact factor: 25.071

8.  Digital technology and COVID-19.

Authors:  Daniel Shu Wei Ting; Lawrence Carin; Victor Dzau; Tien Y Wong
Journal:  Nat Med       Date:  2020-04       Impact factor: 53.440

9.  Blockchain-Based Healthcare Workflow for Tele-Medical Laboratory in Federated Hospital IoT Clouds.

Authors:  Antonio Celesti; Armando Ruggeri; Maria Fazio; Antonino Galletta; Massimo Villari; Agata Romano
Journal:  Sensors (Basel)       Date:  2020-05-02       Impact factor: 3.576

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