Efficient Monitoring and Contact Tracing for COVID-19: A Smart IoT-Based Framework

Roy, Abhishek; Kumbhar, Farooque Hassan; Dhillon, Harpreet S.; Saxena, Navrati; Shin, Soo Young; Singh, Sukhdeep

doi:10.1109/iotm.0001.2000145

Cited by 44 publications

(29 citation statements)

References 14 publications

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“…Roy et al [6] introduce a solution for the contact tracing and monitoring of COVID-19 infection based on Internetof-things (IoT) technology. Device-to-device (D2D) communication technologies are used to exchange information and forward mobile phone data to the healthcare server.…”

Section: A Communication Technologiesmentioning

confidence: 99%

Toward Agile Information and Communication Framework for the Post-COVID-19 Era

Peng

et al. 2021

IEEE Open J. Comput. Soc.

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In order to satisfy new normal life styles in the post-COVID-19 era, an efficient information and communication technology (ICT) framework is required to collect, process, and utilize data for the purpose of satisfying increasing user demand in communications and computing while providing a functionality of responding quickly to pandemic. We propose an ICT framework that is capable to support diverse application requirements based on ambient communication, resilient computing, and agile control technologies. Computer simulations are conducted to evaluate the fundamental functionalities of the proposed framework by using a case study where data are exchanged and processed among different network entities in unmanned aerial vehicle (UAV) empowered vehicular environments. The simulation results show that the proposed approach can outperform existing baselines in various conditions.

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Section: A Communication Technologiesmentioning

confidence: 99%

Toward Agile Information and Communication Framework for the Post-COVID-19 Era

Peng

et al. 2021

IEEE Open J. Comput. Soc.

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“…Utilizing the five best algorithms would give effective and accurate identification of potential cases of COVID-19. The authors in [195] introduce a new IoT-based architecture for contact and disease tracing, which specifically incorporates symptom-based detection that has been ignored in the prior art on tracing models. The ability of this framework to meaningfully merge real-time symptom information (from IoT sensor nodes) and confirmed Corona virus cases (from medical tests) gives a quick and proficient method of tracking the disease spread, which is ultimately useful for the scarce resources (e.g., Coronavirus test kits).…”

Section: ) Iot-based Framework and Architecturesmentioning

confidence: 99%

Intelligent COVID-19 Forecasting, Diagnoses and Monitoring Systems: A Survey

Anjum¹,

Asif²,

Kiran³

et al. 2021

Preprint

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<div>To date, the novel Corona virus (SARS-CoV-2) has infected millions and has caused the deaths of thousands of people around the world. At the moment, five antibodies, two from China, two from the U.S., and one from the UK, have already been widely utilized and numerous vaccines are under the trail process. In order to reach herd immunity, around 70% of the population would need to be inoculated. It may take several years to hinder the spread of SARS-CoV-2. Governments and concerned authorities have taken stringent measurements such as enforcing partial, complete, or smart lockdowns, building temporary medical facilities, advocating social distancing, and mandating masks in public as well as setting up awareness campaigns. Furthermore, there have been massive efforts in various research areas and a wide variety of tools, technologies and techniques have been explored and developed to combat the war against this pandemic. Interestingly, machine learning algorithms and internet of Things (IoTs) technology are the pioneers in this race. Up till now, several real-time and intelligent COVID-19 forecasting, diagnosing, and monitoring systems have been proposed to tackle the COVID-19 pandemic. In this article based on our extensive literature review, we provide a taxonomy based on the intelligent COVID-19 forecasting, diagnosing, and monitoring systems. We review the available literature extensively under the proposed taxonomy and have analyzed a significantly wide range of machine learning algorithms and IoTs which can be used in predicting the spread of COVID-19 and in diagnosing and monitoring the infected individuals. Furthermore, we identify the challenges and also provide our vision about the future research on COVID-19.</div>

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“…Since December 2019, the COVID-19 pandemic has heavily affected some of the world's most populated countries such as the United States, India, Brazil, and China. As of 20 May 2021, more than 165 million infections in more than 200 countries were reported by the World Health Organization(WHO), 1 with more than 3.42 million deaths and more than 100.2 million people recovered. As the COVID-19 virus is transferred to the human body through droplets, it is recommended to COVID-19 patients to self-isolate at home to reduce the spread of the virus.…”

Section: Introductionmentioning

confidence: 99%

“…As the COVID-19 virus is transferred to the human body through droplets, it is recommended to COVID-19 patients to self-isolate at home to reduce the spread of the virus. Around 80 percent of COVID-19 affected patients recovered while staying at home following advice from medical professionals [1]. Thus, it is vital to have the technology and procedures to remotely monitor COVID-19 patients during their home isolation period.…”

Section: Introductionmentioning

confidence: 99%