Intelligent Monitoring System to Aid in the Proactive and Early Detection of People Infected by COVID-19

Chakkor, Saad; Baghouri, Mostafa; Oualkadi, Ahmed El; Hangouche, Abdelkader Jalil El; Laamech, Jawhar; Belfkih, Rachid

doi:10.1007/978-3-030-69744-0_22

Cited by 2 publications

(2 citation statements)

References 9 publications

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“…Electroencephalogram (EEG) sensor [98], pulse oximeter [99], electromyography (EMG) sensor [100], etc., help in the collecting real-time medical health parameters. The data of locations where COVID-19 symptoms are detected is generated by GPS sensors [40] with thermal imaging technology [101]. IoMT sensors are also used in cov-AID for tracking the origin of the outbreak and help people to identify COVID-19 positive patients, ask them to maintain saved distance, and complete the quarantine period.…”

Section: Big Data Generation Layermentioning

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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Section: Big Data Generation Layermentioning

confidence: 99%

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

et al. 2022

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“…IoT devices are able to measure specific human physiological parameters such as heart rate (HR), respiration rate (RR) and blood pressure (BP), electrocardiogram (ECG), Electroencephalogram (EEG), electromyography (EMG), body temperature, Oxygen levels, blood glucose (BG), and the volume of air inspired and expired by lungs (Swayamsiddha and Mohanty, 2020;Chakkor et al, 2021b;Zhang et al, 2021), so that the early diagnosis and necessary treatment can be given One proposed system leverages IoT devices as part of its architecture to actively monitor users data and send this data to heath care centers for evaluation. Also, there are relatively new measurements that monitor the users' heart rate, number of daily steps and sleep time to scan pre-symptomatic cases of COVID-19 for the same purpose-early diagnosis and timely necessary treatment (Josephine et al, 2020;Lo and Sim, 2021;Ni et al, 2021b;Dadon et al, 2022).…”

Section: Detection and Monitoringmentioning

confidence: 99%

A survey of COVID-19 detection and prediction approaches using mobile devices, AI, and telemedicine

Shen

Ghatti

Levkov

et al. 2022

Front. Artif. Intell.

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Since 2019, the COVID-19 pandemic has had an extremely high impact on all facets of the society and will potentially have an everlasting impact for years to come. In response to this, over the past years, there have been a significant number of research efforts on exploring approaches to combat COVID-19. In this paper, we present a survey of the current research efforts on using mobile Internet of Thing (IoT) devices, Artificial Intelligence (AI), and telemedicine for COVID-19 detection and prediction. We first present the background and then present current research in this field. Specifically, we present the research on COVID-19 monitoring and detection, contact tracing, machine learning based approaches, telemedicine, and security. We finally discuss the challenges and the future work that lay ahead in this field before concluding this paper.

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Intelligent Monitoring System to Aid in the Proactive and Early Detection of People Infected by COVID-19

Cited by 2 publications

References 9 publications

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

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

A survey of COVID-19 detection and prediction approaches using mobile devices, AI, and telemedicine

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