Emerging Technologies for COVID‐19

Anand, Rohit; Sindhwani, Nidhi; Saini, Avinash; Shubham, .

doi:10.1002/9781119769088.ch9

Cited by 39 publications

(4 citation statements)

References 34 publications

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“…It is the union of wireless networking, software processing, and computer networking. Internet of Things combines various physical things such as buildings, vehicles, and dissimilar devices embedded with intelligent sensors and allows these objects to exchange and collect data [ 4 , 5 , 35 – 39 ]. The aim of using IIoT is to share information and data all around the world.…”

Section: The Proposed System Modelmentioning

confidence: 99%

“…Physical distancing, repeated hand sanitizing, and face masking have proven to be quite efficient to control the spreading of the virus, but everyone is not obeying the guidelines. Various technologies like machine learning (ML) algorithms [ 1 ], artificial intelligence (AI) approaches [ 1 ], Internet of things (IoT) [ 2 – 5 ], and unmanned aerial vehicles (UAV) [ 6 ] give a real-time scenario at any given point about (i) the number of people following physical distancing and (ii) whether people are wearing masks or not.…”

Section: Introductionmentioning

confidence: 99%

“…In today's scenario, COVID-19 [ 3 , 5 ] has come to be one of the most important topics that ought to be confronted properly. Therefore, there is a requirement to develop an approach that can tackle the issues like unmasked persons and nonmaintenance of physical distancing.…”

Section: Introductionmentioning

confidence: 99%

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Mask Detection and Social Distance Identification Using Internet of Things and Faster R-CNN Algorithm

Meivel¹,

Sindhwani

Anand³

et al. 2022

Computational Intelligence and Neuroscience

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The drones can be used to detect a group of people who are unmasked and do not maintain social distance. In this paper, a deep learning-enabled drone is designed for mask detection and social distance monitoring. A drone is one of the unmanned systems that can be automated. This system mainly focuses on Industrial Internet of Things (IIoT) monitoring using Raspberry Pi 4. This drone automation system sends alerts to the people via speaker for maintaining the social distance. This system captures images and detects unmasked persons using faster regions with convolutional neural network (faster R-CNN) model. When the system detects unmasked persons, it sends their details to respective authorities and the nearest police station. The built model covers the majority of face detection using different benchmark datasets. OpenCV camera utilizes 24/7 service reports on a daily basis using Raspberry Pi 4 and a faster R-CNN algorithm.

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Section: The Proposed System Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Mask Detection and Social Distance Identification Using Internet of Things and Faster R-CNN Algorithm

Meivel¹,

Sindhwani

Anand³

et al. 2022

Computational Intelligence and Neuroscience

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“…Mbunge et al [46] reviewed robotics, IoMT, smart applications, 5G technologies, blockchain, telemedicine, big data, artificial intelligence (AI), geospatial technology, and additive manufacturing as emerging technologies for combating COVID-19, focusing on features, challenges, and domiciliation country. Anand et al [47] examined emerging technology for dealing with pandemic threats. Virtual reality, 5G, artificial intelligence, the Internet of Healthcare Things, wearable sensing, mobile APK, drone facilities, and blockchain are examples of upcoming technologies that can address these important concerns.…”

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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