IoT Platform for COVID-19 Prevention and Control: A Survey
- URL: http://arxiv.org/abs/2010.08056v2
- Date: Thu, 29 Oct 2020 18:04:14 GMT
- Title: IoT Platform for COVID-19 Prevention and Control: A Survey
- Authors: Yudi Dong and Yu-Dong Yao
- Abstract summary: coronavirus disease 2019 (COVID-19) has evolved into an unprecedented pandemic.
Internet of things (IoT) platform is preferred to be utilized to achieve this goal.
This paper presents how the IoT could be incorporated into the epidemic prevention and control system.
- Score: 6.889788474065788
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: As a result of the worldwide transmission of severe acute respiratory
syndrome coronavirus 2 (SARS-CoV-2), coronavirus disease 2019 (COVID-19) has
evolved into an unprecedented pandemic. Currently, with unavailable
pharmaceutical treatments and vaccines, this novel coronavirus results in a
great impact on public health, human society, and global economy, which is
likely to last for many years. One of the lessons learned from the COVID-19
pandemic is that a long-term system with non-pharmaceutical interventions for
preventing and controlling new infectious diseases is desirable to be
implemented. Internet of things (IoT) platform is preferred to be utilized to
achieve this goal, due to its ubiquitous sensing ability and seamless
connectivity. IoT technology is changing our lives through smart healthcare,
smart home, and smart city, which aims to build a more convenient and
intelligent community. This paper presents how the IoT could be incorporated
into the epidemic prevention and control system. Specifically, we demonstrate a
potential fog-cloud combined IoT platform that can be used in the systematic
and intelligent COVID-19 prevention and control, which involves five
interventions including COVID-19 Symptom Diagnosis, Quarantine Monitoring,
Contact Tracing & Social Distancing, COVID-19 Outbreak Forecasting, and
SARS-CoV-2 Mutation Tracking. We investigate and review the state-of-the-art
literatures of these five interventions to present the capabilities of IoT in
countering against the current COVID-19 pandemic or future infectious disease
epidemics.
Related papers
- A Review on the State of the Art in Non Contact Sensing for COVID-19 [9.658514673601326]
COVID-19 disease, caused by SARS-CoV-2, has resulted in a global pandemic recently.
Governments around the world have issued guidance to their citizens to remain at home in efforts to control the spread of the disease.
The goal of controlling the spread of the virus is to prevent strain on hospital.
arXiv Detail & Related papers (2020-07-28T11:18:38Z) - COVID-19 Remote Patient Monitoring: Social Impact of AI [0.0]
A primary indicator of success in the fight against COVID-19 is avoiding stress on critical care infrastructure and services.
There are also secondary considerations for success: mitigating economic damage; curbing the spread of misinformation, improving morale, and preserving a sense of control.
Here, we focus on the effective use of readily available technology to improve the primary and secondary success criteria for the fight against SARS-CoV-2.
arXiv Detail & Related papers (2020-07-24T01:09:56Z) - Understanding the temporal evolution of COVID-19 research through
machine learning and natural language processing [66.63200823918429]
The outbreak of the novel coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been continuously affecting human lives and communities around the world.
We used multiple data sources, i.e., PubMed and ArXiv, and built several machine learning models to characterize the landscape of current COVID-19 research.
Our findings confirm the types of research available in PubMed and ArXiv differ significantly, with the former exhibiting greater diversity in terms of COVID-19 related issues.
arXiv Detail & Related papers (2020-07-22T18:02:39Z) - Internet of Things for Current COVID-19 and Future Pandemics: An
Exploratory Study [4.785691596724824]
The Internet of Things (IoT) has drawn convincing research ground as a new research topic in a wide variety of academic and industrial disciplines.
The current global challenge of the pandemic caused by the novel severe contagious respiratory syndrome coronavirus 2 presents the greatest global public health crisis since the pandemic outbreak of 1918.
The number of diagnosed COVID-19 cases around the world had reached more than 31 million.
arXiv Detail & Related papers (2020-07-22T00:37:24Z) - Future Smart Connected Communities to Fight COVID-19 Outbreak [0.0]
We envision an IoT-enabled ecosystem for intelligent monitoring, pro-active prevention and control, and mitigation of COVID-19.
We propose different architectures, applications and technology systems for various smart infrastructures including E-health, smart home, smart supply chain management, smart locality, and smart city.
arXiv Detail & Related papers (2020-07-20T21:07:53Z) - A Survey on Applications of Artificial Intelligence in Fighting Against
COVID-19 [75.84689958489724]
The COVID-19 pandemic caused by the SARS-CoV-2 virus has spread rapidly worldwide, leading to a global outbreak.
As a powerful tool against COVID-19, artificial intelligence (AI) technologies are widely used in combating this pandemic.
This survey presents medical and AI researchers with a comprehensive view of the existing and potential applications of AI technology in combating COVID-19.
arXiv Detail & Related papers (2020-07-04T22:48:15Z) - The challenges of deploying artificial intelligence models in a rapidly
evolving pandemic [10.188172055060544]
We argue that both basic and applied research are essential to accelerate the potential of AI models.
This perspective may provide a glimpse into how the global scientific community should react to combat future disease outbreaks more effectively.
arXiv Detail & Related papers (2020-05-19T21:11:48Z) - Remote health monitoring and diagnosis in the time of COVID-19 [51.01158603315544]
Coronavirus disease (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
Pandemic has driven incentives to innovate and enhance or create new routes for providing healthcare services at distance.
arXiv Detail & Related papers (2020-05-18T08:54:38Z) - COVID-DA: Deep Domain Adaptation from Typical Pneumonia to COVID-19 [92.4955073477381]
The outbreak of novel coronavirus disease 2019 (COVID-19) has already infected millions of people and is still rapidly spreading all over the globe.
Deep learning has been used recently as effective computer-aided means to improve diagnostic efficiency.
We propose a new deep domain adaptation method for COVID-19 diagnosis, namely COVID-DA.
arXiv Detail & Related papers (2020-04-30T03:13:40Z) - Digital Ariadne: Citizen Empowerment for Epidemic Control [55.41644538483948]
The COVID-19 crisis represents the most dangerous threat to public health since the H1N1 pandemic of 1918.
Technology-assisted location and contact tracing, if broadly adopted, may help limit the spread of infectious diseases.
We present a tool, called 'diAry' or 'digital Ariadne', based on voluntary location and Bluetooth tracking on personal devices.
arXiv Detail & Related papers (2020-04-16T15:53:42Z) - Mapping the Landscape of Artificial Intelligence Applications against
COVID-19 [59.30734371401316]
COVID-19, the disease caused by the SARS-CoV-2 virus, has been declared a pandemic by the World Health Organization.
We present an overview of recent studies using Machine Learning and, more broadly, Artificial Intelligence to tackle many aspects of the COVID-19 crisis.
arXiv Detail & Related papers (2020-03-25T12:30:33Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.