A Systematic Review and IoMT Based Big Data Framework for COVID-19 Prevention and Detection
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 t...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-09-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/11/17/2777 |
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| author | Soomaiya Hamid Narmeen Zakaria Bawany Ali Hassan Sodhro Abdullah Lakhan Saleem Ahmed |
| author_facet | Soomaiya Hamid Narmeen Zakaria Bawany Ali Hassan Sodhro Abdullah Lakhan Saleem Ahmed |
| author_sort | Soomaiya Hamid |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T01:54:30Z |
| format | Article |
| id | doaj.art-e99b24d8736346f1bf9089fdcaa8b230 |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-10T01:54:30Z |
| publishDate | 2022-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-e99b24d8736346f1bf9089fdcaa8b2302023-11-23T12:59:51ZengMDPI AGElectronics2079-92922022-09-011117277710.3390/electronics11172777A Systematic Review and IoMT Based Big Data Framework for COVID-19 Prevention and DetectionSoomaiya Hamid0Narmeen Zakaria Bawany1Ali Hassan Sodhro2Abdullah Lakhan3Saleem Ahmed4Center for Computing Research, Department of Computer Science and Software Engineering, Jinnah University for Women, Karachi 74600, PakistanCenter for Computing Research, Department of Computer Science and Software Engineering, Jinnah University for Women, Karachi 74600, PakistanDepartment of Computer Science, Kristianstad University, SE-21988 Kristianstad, SwedenDepartment of Computer Science, Dawood University of Engineering and Technology, Karachi 74800, PakistanDepartment of Computer System Engineering, Dawood University of Engineering & Technology Karachi, Karachi 74800, PakistanThe 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.https://www.mdpi.com/2079-9292/11/17/2777IoMTInternet of Medical Thingsbig data frameworkremote diagnosisremote patient monitoringCOVID-19 outbreak detection |
| spellingShingle | Soomaiya Hamid Narmeen Zakaria Bawany Ali Hassan Sodhro Abdullah Lakhan Saleem Ahmed A Systematic Review and IoMT Based Big Data Framework for COVID-19 Prevention and Detection Electronics IoMT Internet of Medical Things big data framework remote diagnosis remote patient monitoring COVID-19 outbreak detection |
| title | A Systematic Review and IoMT Based Big Data Framework for COVID-19 Prevention and Detection |
| title_full | A Systematic Review and IoMT Based Big Data Framework for COVID-19 Prevention and Detection |
| title_fullStr | A Systematic Review and IoMT Based Big Data Framework for COVID-19 Prevention and Detection |
| title_full_unstemmed | A Systematic Review and IoMT Based Big Data Framework for COVID-19 Prevention and Detection |
| title_short | A Systematic Review and IoMT Based Big Data Framework for COVID-19 Prevention and Detection |
| title_sort | systematic review and iomt based big data framework for covid 19 prevention and detection |
| topic | IoMT Internet of Medical Things big data framework remote diagnosis remote patient monitoring COVID-19 outbreak detection |
| url | https://www.mdpi.com/2079-9292/11/17/2777 |
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