Review of Recent Technologies for Tackling COVID-19

Alharbi, Ayman; Rahman, Mahbubur

doi:10.1007/s42979-021-00841-z

Cited by 4 publications

(4 citation statements)

References 158 publications

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“…As part of diagnosing the condition, distinct criteria needed to be defined and met. Lung and infectious disease experts have noted that an especially unique factor of COVID-19 patients is the sound of their breathing, speaking, and dry coughing [21][22][23][24]. To diagnose patients' conditions and create tools that can diagnose them in physician-lacking settings, scientists have created machine-learning algorithms.…”

Section: Figure 4: (A) Insertion Time and Memory Usage (B) Retrieval ...mentioning

confidence: 99%

Using Ethereum Smart Contracts to Store and Share COVID-19 Patient Data

Batchu¹,

Patel²,

Henry³

et al. 2022

Cureus

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The emergence and rapid spread of the coronavirus disease 2019 (COVID-19) pandemic have revealed the limitations in current healthcare systems to handle patient records securely and transparently, and novel protocols are required to address these shortcomings. An attractive option is the use of Ethereum smart contracts to secure the storage of medical records and concomitant data logs. Ethereum is an open-source platform that can be used to construct smart contracts, which are collections of code that allow transactions under certain parameters and are self-executable. MethodsThe present study developed a proof-of-concept smart contract that stores COVID-19 patient data such as the patient identifier (ID), variant, chest CT grade, and significant comorbidities. A sample, fictitious patient data for the purpose of testing was configured to a private network. A smart contract was created in the Ethereum state and tested by measuring the time to insert and query patient data. ResultsTesting with a private, Proof of Authority (PoA) network required only 191 milliseconds and 890 MB of memory per insertion to insert 50 records while inserting 350 records required 674 milliseconds and similar memory per insertion, as memory per insertion was nearly constant with the increasing number of records inserted. Retrieving required 912 MB for a query involving all three fields and no wildcards in a 350-record database. Only 883 MB was needed to procure a similar observation from a 50-record database. ConclusionThis study exemplifies the use of smart contracts for efficient retrieval/insertion of COVID-19 patient data and provides a case use of secure and efficient data logging for sensitive COVID-19 data.

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Section: Figure 4: (A) Insertion Time and Memory Usage (B) Retrieval ...mentioning

confidence: 99%

Using Ethereum Smart Contracts to Store and Share COVID-19 Patient Data

Batchu¹,

Patel²,

Henry³

et al. 2022

Cureus

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“…The uses of IoT and AI in clinical medicine are thoroughly summarized, the major hurdles are assessed, and future trends and advances were also discussed in numerous studies. Alharbi et al [41] examine current attempts to address the COVID-19 problem using technology improvements, including IoMT. M. Hasnain et al [42] offer an overview of recent research on frontline medical worker safety concerns and how technology is being used to combat the COVID-19 epidemic.…”

Section: Review: Iot or Iomt Including Covid-19mentioning

confidence: 99%

A Systematic Review and IoMT Based Big Data Framework for COVID-19 Prevention and Detection

et al. 2022

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The Internet of Medical Things (IoMT) is transforming modern healthcare systems by merging technological, economical, and social opportunities and has recently gained traction in the healthcare domain. The severely contagious respiratory syndrome coronavirus called COVID-19 has emerged as a severe threat to public health. COVID-19 is a highly infectious virus that is spread by person-to-person contact. Therefore, minimizing physical interactions between patients and medical healthcare workers is necessary. The significance of technology and its associated potential were fully explored and proven during the outbreak of COVID-19 in all domains of human life. Healthcare systems employ all modes of technology to facilitate the increasing number of COVID-19 patients. The need for remote healthcare was reemphasized, and many remote healthcare solutions were adopted. Various IoMT-based systems were proposed and implemented to support traditional healthcare systems with reaching the maximum number of people remotely. The objective of this research is twofold. First, a systematic literature review (SLR) is conducted to critically evaluate 76 articles on IoMT systems for different medical applications, especially for COVID-19 and other health sectors. Secondly, we briefly review IoMT frameworks and the role of IoMT-based technologies in COVID-19 and propose a framework, named ‘cov-AID’, that remotely monitors and diagnoses the disease. The proposed framework encompasses the benefits of IoMT sensors and extensive data analysis and prediction. Moreover, cov-AID also helps to identify COVID-19 outbreak regions and alerts people not to visit those locations to prevent the spread of infection. The cov-AID is a promising framework for dynamic patient monitoring, patient tracking, quick disease diagnosis, remote treatment, and prevention from spreading the virus to others. We also discuss potential challenges faced in adopting and applying big data technologies to combat COVID-19.

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“…5G telecommunication networks, IoMT, and data analysis methods with machine-learning algorithms are currently used in different areas of health science, epidemiology, pharmacy, and virology to overcome the damage caused by pathogens [ 8 ]. Coronavirus is a respiratory illness that affects breathing patterns and other vital parameters.…”

Section: Introductionmentioning

confidence: 99%

Advanced Mobile Communication Techniques in the Fight against the COVID-19 Pandemic Era and Beyond: An Overview of 5G/B5G/6G

Lin,

Chang

2023

Sensors

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The coronavirus disease 2019 (COVID-19) pandemic has severely affected people’s lives worldwide in an unexpected manner. According to the World Health Organization (WHO), several viral epidemics continue to occur and pose a significant public health problem. Until May 2023, there have been 676 million cases of COVID-19 infections and over 6.8 million deaths, globally. This paper surveys the role and effectiveness of advanced fifth-generation (5G)/beyond 5G (B5G)/sixth-generation (6G) technologies, combined with mobile applications (apps) and the Internet of Medical Things (IoMT), in detecting, managing, and mitigating the spread of COVID-19 and designing smart healthcare infrastructures for future pandemics. Analyzing and summarizing the research of relevant scholars based on the impact of 5G/B5G/6G and other technologies on COVID-19. The study tabulates the technical characteristics and effectiveness of different technologies in the context of COVID-19, summarizing the research of previous scholars. Challenges and design issues in the implementation of advanced information and telecommunication systems were demonstrated. These technologies can inspire the design of smart healthcare infrastructures to combat future virus pandemics.

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Review of Recent Technologies for Tackling COVID-19

Cited by 4 publications

References 158 publications

Using Ethereum Smart Contracts to Store and Share COVID-19 Patient Data

Using Ethereum Smart Contracts to Store and Share COVID-19 Patient Data

A Systematic Review and IoMT Based Big Data Framework for COVID-19 Prevention and Detection

Advanced Mobile Communication Techniques in the Fight against the COVID-19 Pandemic Era and Beyond: An Overview of 5G/B5G/6G

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