Search Advanced

Mathematical Biosciences and Engineering

2021, Volume 18, Issue 6: 9697-9726. doi: 10.3934/mbe.2021475
Previous Article Next Article
Survey Special Issues

Study on IoT for SARS-CoV-2 with healthcare: present and future perspective

  • 1.
    Department of Computer Science and Engineering, National Institute of Textile Engineering and Research (NITER), Constituent Institute of Dhaka University, Savar, Dhaka-1350, Bangladesh
  • 2.
    Department of Computer Science and Engineering, Mawlana Bhashani Science and Technology University, Tangail, Bangladesh
  • 3.
    Department of Electrical and Electronic Engineering, National Institute of Textile Engineering and Research (NITER), Constituent Institute of Dhaka University, Savar, Dhaka-1350, Bangladesh
  • 4.
    Future Technology Research Center, College of Future, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin 64002, Taiwan
  • 5.
    Dept. of Computer Science, Texas A & M University-Corpus Christi, 6300 Ocean Drive, Corpus Christi, Texas, USA, 78412

  • Academic Editor: Yang Kuang
  • Received: 18 August 2021 Accepted: 13 October 2021 Published: 04 November 2021

  • The ever-evolving and contagious nature of the Coronavirus (COVID-19) has immobilized the world around us. As the daily number of infected cases increases, the containment of the spread of this virus is proving to be an overwhelming task. Healthcare facilities around the world are overburdened with an ominous responsibility to combat an ever-worsening scenario. To aid the healthcare system, Internet of Things (IoT) technology provides a better solution—tracing, testing of COVID patients efficiently is gaining rapid pace. This study discusses the role of IoT technology in healthcare during the SARS-CoV-2 pandemics. The study overviews different research, platforms, services, products where IoT is used to combat the COVID-19 pandemic. Further, we intelligently integrate IoT and healthcare for COVID-19 related applications. Again, we focus on a wide range of IoT applications in regards to SARS-CoV-2 tracing, testing, and treatment. Finally, we effectively consider further challenges, issues, and some direction regarding IoT in order to uplift the healthcare system during COVID-19 and future pandemics.

    Citation: Anichur Rahman, Muaz Rahman, Dipanjali Kundu, Md Razaul Karim, Shahab S. Band, Mehdi Sookhak. Study on IoT for SARS-CoV-2 with healthcare: present and future perspective[J]. Mathematical Biosciences and Engineering, 2021, 18(6): 9697-9726. doi: 10.3934/mbe.2021475

    Related Papers:

  • The ever-evolving and contagious nature of the Coronavirus (COVID-19) has immobilized the world around us. As the daily number of infected cases increases, the containment of the spread of this virus is proving to be an overwhelming task. Healthcare facilities around the world are overburdened with an ominous responsibility to combat an ever-worsening scenario. To aid the healthcare system, Internet of Things (IoT) technology provides a better solution—tracing, testing of COVID patients efficiently is gaining rapid pace. This study discusses the role of IoT technology in healthcare during the SARS-CoV-2 pandemics. The study overviews different research, platforms, services, products where IoT is used to combat the COVID-19 pandemic. Further, we intelligently integrate IoT and healthcare for COVID-19 related applications. Again, we focus on a wide range of IoT applications in regards to SARS-CoV-2 tracing, testing, and treatment. Finally, we effectively consider further challenges, issues, and some direction regarding IoT in order to uplift the healthcare system during COVID-19 and future pandemics.


    加载中


    [1] T. Singhal, A review of coronavirus disease-2019 (COVID-19), Indian J. Pediatr., 87 (2020), 281–286. doi: 10.1007/s12098-020-03263-6
    [2] N. Chen, M. Zhou, X. Dong, J. Qu, F. Gong, Y. Han, et al., Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study, Lancet, 395 (2020), 507–513. doi: 10.1016/S0140-6736(20)30211-7
    [3] I. Valverde, Y. Singh, J. Sanchez-de Toledo, P. Theocharis, A. Chikermane, S. Di Filippo, et al., Acute cardiovascular manifestations in 286 children with multisystem inflammatory syndrome associated with COVID-19 infection in Europe, Circulation, 143 (2021), 21–32. doi: 10.1161/CIRCULATIONAHA.120.050065
    [4] J. Riou, C. L. Althaus, Pattern of early human-to-human transmission of Wuhan 2019 novel coronavirus (2019-nCoV), December 2019 to January 2020, Eurosurveillance, 25 (2020), 2000058.
    [5] L. Yuan, N. Zhi, C. Yu, G. Ming, L. Yingle, G. N. Kumar, et al., Aerodynamic characteristics and RNA concentration of SARS-CoV-2 aerosol in Wuhan hospitals during COVID-19 outbreak, BioRxiv, 2020.
    [6] N. Van Doremalen, T. Bushmaker, D. H. Morris, M. G. Holbrook, A. Gamble, B. N. Williamson, et al., Aerosol and surface stability of SARS-CoV-2 as compared with SARS-CoV-1, N. Engl. J Med., 382 (2020), 1564–1567. doi: 10.1056/NEJMc2004973
    [7] J. Hellewell, S. Abbott, A. Gimma, N. I. Bosse, C. I. Jarvis, T. W. Russell, et al., Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts, Lancet Global Health, 8 (2020), e488–e496. doi: 10.1016/S2214-109X(20)30074-7
    [8] M. Lotfi, M. R. Hamblin, N. Rezaei, COVID-19: transmission, prevention, and potential therapeutic opportunities, Clin. Chim. Acta, 2020.
    [9] R. P. Singh, M. Javaid, A. Haleem, R. Suman, Internet of things (IoT) applications to fight against COVID-19 pandemic, Diabetes Metab. Syndr. Clin. Res. Rev., 14 (2020), 521–524. doi: 10.1016/j.dsx.2020.04.041
    [10] M. Hasan, A. Rahman, M. J. Islam, Distb-cvs: a distributed secure blockchain based online certificate verification system from bangladesh perspective, in 2020 2nd International Conference on Advanced Information and Communication Technology (ICAICT), (2020), 460–465.
    [11] D. Abid Haleem, M. Javaid, I. H. Khan, B. Tech, Internet of things (IoT) applications in orthopaedics, 2019.
    [12] R. Jiloha, COVID-19 and mental health, Epidemiol. Int. (E-ISSN: 2455-7048), 5 (2020), 7–9.
    [13] A. Haleem, M. Javaid, R. Vaishya, S. Deshmukh, Areas of academic research with the impact of COVID-19, Am. J. Emerg. Med., 38 (2020), 1524–1526. doi: 10.1016/j.ajem.2020.04.022
    [14] K. M. S. Azad, N. Hossain, M. J. Islam, A. Rahman, S. Kabir, Preventive determination and avoidance of ddos attack with sdn over the iot networks. in International Conference on Automation, Control and Mechatronics for Industry 4.0 (ACMI 2021), IEEE, 2021.
    [15] A. Rahman, M. K. Nasir, Z. Rahman, A. Mosavi, S. Shahab, B. Minaei-Bidgoli, Distblockbuilding: a distributed blockchain-based sdn-iot network for smart building management, IEEE Access, 8 (2020), 140008–140018. doi: 10.1109/ACCESS.2020.3012435
    [16] M. Mohammed, H. Syamsudin, S. Al-Zubaidi, R. R. AKS, E. Yusuf, Novel COVID-19 detection and diagnosis system using iot based smart helmet, Int. J. Psychosoc. Rehabil., 24 (2020), 2296–2303.
    [17] D. Darma, Z. Ilmi, S. Darma, Y. Syaharuddin, COVID-19 and its impact on education: challenges from industry 4.0, 2020.
    [18] Z. Ilmi, D. C. Darma, M. Azis, Independence in learning, education management, and industry 4.0: habitat indonesia during COVID-19, J. Anthropol. Sport Phys. Educ., 4 (2020), 63–66.
    [19] K. Kumar, N. Kumar, R. Shah, Role of IoT to avoid spreading of COVID-19, Int. J. Intell. Networks, 1 (2020), 32–35. doi: 10.1016/j.ijin.2020.05.002
    [20] K. Farsalinos, K. Poulas, D. Kouretas, A. Vantarakis, M. Leotsinidis, D. Kouvelas, et al., Improved strategies to counter the COVID-19 pandemic: lockdowns vs. primary and community healthcare, Toxicol. Rep., 8 (2021), 1–9. doi: 10.1016/j.toxrep.2020.12.001
    [21] Centers for Disease Control and Prevention, Coronavirus Disease 2019: COVID-19, 2020. Available from: https://www.cdc.gov/coronavirus/2019-ncov/index.html.
    [22] L. H. Nguyen, D. A. Drew, M. S. Graham, A. D. Joshi, C. G. Guo, W. Ma, et al., Risk of COVID-19 among front-line health-care workers and the general community: a prospective cohort study, Lancet Public Health, 5 (2020), e475–e483. doi: 10.1016/S2468-2667(20)30164-X
    [23] A. Haleem, M. Javaid, Medical 4.0 and its role in healthcare during COVID-19 pandemic: a review, J. Ind. Integr. Manage., 5 (2020).
    [24] A. Celesti, M. Fazio, F. Galán Márquez, A. Glikson, H. Mauwa, A. Bagula, How to develop IoT cloud e-health systems based on fiware: a lesson learnt, J. Sensor Actuator Networks, 8 (2019), 7. doi: 10.3390/jsan8010007
    [25] S. Debdas, C. K. Panigrahi, P. Kundu, S. Kundu, R. Jha, IoT application in interconnected hospitals, Mach. Learn. Healthcare Appl., (2021), 227.
    [26] A. Albahri, J. K. Alwan, Z. K. Taha, S. F. Ismail, R. A. Hamid, A. Zaidan, et al., IoT-based telemedicine for disease prevention and health promotion: state-of-the-art, J. Network Comput. Appl., 173 (2021), 102873. doi: 10.1016/j.jnca.2020.102873
    [27] M. Shahroz, F. Ahmad, M. S. Younis, N. Ahmad, M. N. K. Boulos, R. Vinuesa, et al., COVID-19 digital contact tracing applications and techniques: a review post initial deployments, preprint, arXiv: 2103.01766.
    [28] S. Mohapatra, S. Mohanty, S. Mohanty, Smart healthcare: an approach for ubiquitous healthcare management using IoT, in Big Data Analytics for Intelligent Healthcare Management, Elsevier, (2019), 175–196.
    [29] A. Rahman, M. J. Islam, Z. Rahman, M. M. Reza, A. Anwar, M. P. Mahmud, et al., Distb-condo: distributed blockchain-based IoT-sdn model for smart condominium, IEEE Access, 8 (2020), 209 594–209 609. doi: 10.1109/ACCESS.2020.3039113
    [30] K. N. Swaroop, K. Chandu, R. Gorrepotu, S. Deb, A health monitoring system for vital signs using IoT, Internet Things, 5 (2019), 116–129. doi: 10.1016/j.iot.2019.01.004
    [31] A. Zamanifar, Remote patient monitoring: health status detection and prediction in IoT-based health care, in IoT in Healthcare and Ambient Assisted Living, Springer, (2021), 89–102.
    [32] A. Rahman, M. J. Islam, M. Saikat Islam Khan, S. Kabir, A. I. Pritom, M. Razaul Karim, Block-sdotcloud: enhancing security of cloud storage through blockchain-based sdn in IoT network, in 2020 2nd International Conference on Sustainable Technologies for Industry 4.0 (STI), (2020), 1–6.
    [33] M. R. Valanarasu, Smart and secure IoT and AI integration framework for hospital environment, J. ISMAC, 1 (2019), 172–179. doi: 10.36548/jismac.2019.3.004
    [34] A. Alamri, Ontology middleware for integration of IoT healthcare information systems in ehr systems, Computers, 7 (2018), 51. doi: 10.3390/computers7040051
    [35] T. Wu, F. Wu, C. Qiu, J. M. Redouté, M. R. Yuce, A rigid-flex wearable health monitoring sensor patch for IoT-connected healthcare applications, IEEE Internet Things J., 7 (2020), 6932–6945. doi: 10.1109/JIOT.2020.2977164
    [36] D. Zhang, X. Xia, Y. Yang, P. Yang, C. Xie, M. Cui, et al., A novel word similarity measure method for IoT-enabled healthcare applications, Future Gener. Comput. Syst., 114 (2021), 209–218. doi: 10.1016/j.future.2020.07.053
    [37] S. Selvaraj, S. Sundaravaradhan, Challenges and opportunities in IoT healthcare systems: a systematic review, SN Appl. Sci., 2 (2020), 1–8.
    [38] N. Gupta, S. Gupta, M. Khosravy, N. Dey, N. Joshi, R. G. Crespo, et al., Economic iot strategy: the future technology for health monitoring and diagnostic of agriculture vehicles, J. Int. Manuf., 32 (2021), 1117–1128. doi: 10.1007/s10845-020-01610-0
    [39] P. P. Ray, B. Chowhan, N. Kumar, A. Almogren, Biothr: electronic health record servicing scheme in IoT-blockchain ecosystem, IEEE Internet Things J., 2021.
    [40] M. Javaid, I. H. Khan, Internet of things (IoT) enabled healthcare helps to take the challenges of COVID-19 pandemic, J. Oral Biol. Craniofacial Res., 11 (2021), 209–214. doi: 10.1016/j.jobcr.2021.01.015
    [41] I. de Morais Barroca Filho, G. Aquino, R. S. Malaquias, G. Girão, S. R. M. Melo, An IoT-based healthcare platform for patients in ICU beds during the COVID-19 outbreak, IEEE Access, 9 (2021), 27262–27277. doi: 10.1109/ACCESS.2021.3058448
    [42] A. Islam, S.Y. Shin, A blockchain-based secure healthcare scheme with the assistance of unmanned aerial vehicle in Internet of Things, Comput. Electr. Eng., 84 (2020), 106627. doi: 10.1016/j.compeleceng.2020.106627
    [43] A. Islam, T. Rahim, M. D. Masuduzzaman, S. Y. Shin, A blockchain-based artificial intelligence-empowered contagious pandemic situation supervision scheme using internet of drone things. IEEE Wireless Commun., 2021.
    [44] M. Elhoseny, G. Ramírez-González, O. M. Abu-Elnasr, S. A. Shawkat, N. Arunkumar, A. Farouk, Secure medical data transmission model for IoT-based healthcare systems, IEEE Access, 6 (2018), 20 596–20 608. doi: 10.1109/ACCESS.2018.2817615
    [45] S. Pirbhulal, N. Pombo, V. Felizardo, N. Garcia, A. H. Sodhro, S. C. Mukhopadhyay, Towards machine learning enabled security framework for IoT-based healthcare, in 2019 13th International Conference on Sensing Technology (ICST), IEEE, (2019), 1–6.
    [46] S. Saha, A. K. Sutrala, A. K. Das, N. Kumar, J. J. Rodrigues, On the design of blockchain-based access control protocol for IoT-enabled healthcare applications, in ICC 2020-2020 IEEE International Conference on Communications (ICC), IEEE, 2020, 1–6.
    [47] S. S. Sahoo, S. Mohanty, B. Majhi, A secure three factor based authentication scheme for health care systems using IoT enabled devices, J. Ambient Intell. Humanized Comput., 12 (2021), 1419–1434. doi: 10.1007/s12652-020-02213-6
    [48] A. Hussain, T. Ali, F. Althobiani, U. Draz, M. Irfan, S. Yasin, et al., Security framework for IoT based real-time health applications, Electronics, 10 (2021), 719. doi: 10.3390/electronics10060719
    [49] World Health Organization, 2020. Digital technology for COVID-19 response, Available from: https://www.who.int/news/item/03-04-2020-digital-technology-for-covid-19-response.
    [50] A. Gatouillat, Y. Badr, B. Massot, E. Sejdić, Internet of medical things: a review of recent contributions dealing with cyber-physical systems in medicine, IEEE Internet Things J., 5 (2018), 3810–3822. doi: 10.1109/JIOT.2018.2849014
    [51] L. Wynants, B. Van Calster, G. S. Collins, R. D. Riley, G. Heinze, E. Schuit, et al., Prediction models for diagnosis and prognosis of COVID-19: systematic review and critical appraisal, BMJ, 369 (2020).
    [52] L. Yuan, W. Yeung, L. Celi, Urban intelligence for pandemic response, JMIR Public Health Surveill., 2020.
    [53] V. Chamola, V. Hassija, V. Gupta, M. Guizani, A comprehensive review of the COVID-19 pandemic and the role of IoT, Drones, AI, Blockchain, and 5G in managing its impact, IEEE Access, 8 (2020), 90 225–90 265. doi: 10.1109/ACCESS.2020.2992341
    [54] Q. V. Pham, D. C. Nguyen, T. Huynh-The, W. J. Hwang, P. N. Pathirana, Artificial intelligence (AI) and big data for coronavirus (COVID-19) pandemic: a survey on the state-of-the-arts, 2020.
    [55] A. A. Ardakani, A. R. Kanafi, U. R. Acharya, N. Khadem, A. Mohammadi, Application of deep learning technique to manage COVID-19 in routine clinical practice using CT images: eesults of 10 convolutional neural networks, Comput. Biol. Med., 121 (2020), 103795. doi: 10.1016/j.compbiomed.2020.103795
    [56] M. A. Elaziz, K. M. Hosny, A. Salah, M. M. Darwish, S. Lu, A. T. Sahlol, New machine learning method for image-based diagnosis of COVID-19, Plos One, 15 (2020), e0235187. doi: 10.1371/journal.pone.0235187
    [57] A. Imran, I. Posokhova, H. N. Qureshi, U. Masood, M. S. Riaz, K. Ali, et al., AI4covid-19: AI enabled preliminary diagnosis for COVID-19 from cough samples via an app, Inf. Med. Unlocked, 20 (2020), 100378. doi: 10.1016/j.imu.2020.100378
    [58] I. Ahmed, A. Ahmad, G. Jeon, An IoT based deep learning framework for early assessment of COVID-19, IEEE Internet Things J., 2020.
    [59] Autonomous robot performs COVID-19 nasal swab tests, 2020. Available from: https://www.hospimedica.com/health-it/articles/294783922/autonomous-robot-performs-covid-19-nasal-swab-tests.html.
    [60] M. Nasajpour, S. Pouriyeh, R. M. Parizi, M. Dorodchi, M. Valero, H. R. Arabnia, Internet of Things for current COVID-19 and future pandemics: an exploratory study, J. Healthcare Inf. Res., (2020), 1–40.
    [61] Visionstate ships first IoT buttons for rapid response to cleaning alerts, 2020. Available from: https://www.globenewswire.com/news-release/2020/03/23/2004645/0/en/Visionstate-Ships-First-IoT-Buttons-for-Rapid-Response-to-Cleaning-Alerts.html.
    [62] S. Obeidat, How artificial intelligence is helping fight the COVID-19 pandemic, Entrepreneur Middle East, 2020.
    [63] M. Schmitt, How to fight COVID-19 with machine learning, 2020. Available from: https://www.datarevenue.com/en-blog/machine-learning-covid-19.
    [64] E. Strickland, AI can help hospitals triage COVID-19 patients, IEEE Spectrum, 2020. Available from: https://spectrum.ieee.org/the-human-os/artificial-intelligence/medical-ai/ai-can-help-hospitals-triage-covid19-patients.
    [65] Kinsa is an early warning system to detect and respond to contagious illness, 2020. Available from: https://kinsahealth.com/.
    [66] T. Tamura, M. Huang, T. Togawa, Current developments in wearable thermometers, Adv. Biomed. Eng., 7 (2018), 88–99. doi: 10.14326/abe.7.88
    [67] P. Vaishnavi, J. Agnishwar, K. Padmanathan, S. Umashankar, T. Preethika, S. Annapoorani, et al., Artificial intelligence and drones to combat COVID-19, Preprints, 2020.
    [68] Media Centre, Working on pandemic drone to detect corona virus, 2020. Available from: https://www.suasnews.com/2020/03/unisa-working-on-pandemic-drone-to-detect-coronavirus/.
    [69] M. Mohammed, N. A. Hazairin, S. Al-Zubaidi, S. A. Karim, S. Mustapha, E. Yusuf, Toward a novel design for coronavirus detection and diagnosis system using IoT based drone technology, Int. J. Psychosoc. Rehabil., 24 (2020), 2287–2295.
    [70] M. Mohammed, N. A. Hazairin, H. Syamsudin, S. Al-Zubaidi, A. Sairah, S. Mustapha, et al., 2019 novel coronavirus disease (COVID-19): detection and diagnosis system using IoT based smart glasses, Int. J. Adv. Sci. Technol., 29 (2020).
    [71] G. Quer, J. M. Radin, M. Gadaleta, K. Baca-Motes, L. Ariniello, E. Ramos, et al., Wearable sensor data and self-reported symptoms for COVID-19 detection, Nat. Med., 27 (2021), 73–77. doi: 10.1038/s41591-020-1123-x
    [72] Estimote wearables track workers to curb COVID-19 outbreak, 2020. Available from: https://www.slashgear.com/estimote-wearables-track-workers-to-curb-covid-19-outbreak-02615366/.
    [73] T. Hornyak, What America can learn from China's use of robots and telemedicine to combat the coronavirus, Tech. Drivers, 2020.
    [74] M. Hollister, AI can help with the COVID-19 crisis-but the right human input is key, in World Economic Forum, 30 (2020).
    [75] R. K. R. Kummitha, Smart technologies for fighting pandemics: the techno-and human-driven approaches in controlling the virus transmission, Gov. Inf. Q., (2020), 101481.
    [76] D. DeCaprio, J. Gartner, T. Burgess, K. Garcia, S. Kothari, S. Sayed, et al., Building a COVID-19 vulnerability index, preprint, arXiv: 2003.07347.
    [77] A. Rahman, M. J. Islam, M. R. Karim, D. Kundu, S. Kabir, An intelligent vaccine distribution process in COVID-19 pandemic through blockchain-sdn framework from bangladesh perspective, in International Conference on Electronics, Communications and Information Technology 2021 (ICECIT 2021), 2021.
    [78] M. Zastrow, Coronavirus contact-tracing apps: can they slow the spread of COVID-19? Nature, 2020.
    [79] Z. Geng, X. Zhang, Z. Fan, X. Lv, Y. Su, H. Chen, Recent progress in optical biosensors based on smartphone platforms, Sensors, 17 (2017), 2449. doi: 10.3390/s17112449
    [80] T. Wright, Blockchain app used to track COVID-19 cases in Latin America, Coin Telegraph Future Money, 6 (2020).
    [81] Ministry of Health, HaMagen 2.0: together we can defeat COVID-19, Available from: https://govextra.gov.il/ministry-of-health/hamagen-app/download-en/.
    [82] C. Chong, About 1 million people have downloaded tracetogether app, but more need to do so for it to be effective: lawrence wong, Straits Times, 2020.
    [83] L. Kelion, Coronavirus: moscow rolls out patient-tracking app, 2020.
    [84] A. Rahman, C. Chakraborty, A. Anwar, M. Karim, M. Islam, D. Kundu, et al., Sdn–IoT empowered intelligent framework for industry 4.0 applications during COVID-19 pandemic, Cluster Comput., (2021), 1–18.
    [85] Teladochealth, Whole-Person: virtual care for all, Available from: https://www.teladochealth.com/.
    [86] A. Chakraborty, Assam: telemedicine, video monitoring for COVID-19 home quarantined people in Dhemaji, 2020.
    [87] D. O'Keeffe, A World First as Drone delivers medication to the Aran Islands, 2019.
    [88] J. Yang, T. Reuter, Three ways China is using drones to fight coronavirus, in World Economic Forum, 16 (2020).
    [89] E. Ackerman, Zipline wants to bring medical drone delivery to us to fight COVID-19, IEEE Spectrum N. Y. NY USA, 2020.
    [90] S. Sahasranamam, How coronavirus sparked a wave of innovation in India, in World Economic Forum, 2020.
    [91] M. Javaid, A. Haleem, R. Vaishya, S. Bahl, R. Suman, A. Vaish, Industry 4.0 technologies and their applications in fighting COVID-19 pandemic, Diabetes Metab. Syndr. Clin. Res. Rev., 14 (2020), 419–422. doi: 10.1016/j.dsx.2020.06.065
    [92] A. Ghimire, S. Thapa, A. K. Jha, A. Kumar, A. Kumar, S. Adhikari, AI and IoT solutions for tackling COVID-19 pandemic, in 2020 4th International Conference on Electronics, Communication and Aerospace Technology (ICECA), IEEE, (2020), 1083–1092.
    [93] L. Bai, D. Yang, X. Wang, L. Tong, X. Zhu, N. Zhong, et al., Chinese experts' consensus on the Internet of things-aided diagnosis and treatment of coronavirus disease 2019 (COVID-19), Clin. eHealth, 3 (2020), 7–15. doi: 10.1016/j.ceh.2020.03.001
    [94] M. J. Islam, A. Rahman, S. Kabir, M. R. Karim, U. K. Acharjee, M. K. Nasir, et al., Blockchain-sdn based energy-aware and distributed secure architecture for IoTs in smart cities, IEEE Internet Things J., (2021), 1.
    [95] World Certification Institute, How next-generation information technologies tackled COVID-19 in China, 2020. Available from: https://www.worldcertification.org/how-next-generation-information-technologies-tackled-covid-19-china/.
    [96] H. H. Elmousalami, A. Darwish, A. E. Hassanien, The truth about 5G and COVID-19: basics, analysis, and opportunities, in Digital Transformation and Emerging Technologies for Fighting COVID-19 Pandemic: Innovative Approaches, (2021), 249–259, .
    [97] A. Rahman, U. Sara, D. Kundu, S. Islam, M. J. Islam, M. Hasan, et al., Distb-sdoindustry: enhancing security in industry 4.0 services based on distributed blockchain through software defined networking-IoT enabled architecture, Int. J. Adv. Comput. Sci. Appl., 11 (2020).
    [98] S. Jaafari, A. Alhasani, S. M. Almutairi, E. Alghosn, R. Alfahhad, Certain investigations on IoT system for COVID-19, in 2020 International Conference on Computing and Information Technology (ICCIT-1441), IEEE, (2020), 1–4.
    [99] R. Stojanović, A. Škraba, B. Lutovac, A headset like wearable device to track COVID-19 symptoms, in 2020 9th Mediterranean Conference on Embedded Computing (MECO), IEEE, (2020), 1–4.
    [100] Researchers use open-source software to improve COVID-19 screening with AI, 2020. Available from: https://uwaterloo.ca/news/news/researchers-use-open-source-software-improve-covid-19.
    [101] B. Marr, Robots and drones are now used to fight COVID-19, 2020.
    [102] Delhi civic body begins thermal screening people on balconies with drones, 2020. Available from: https://www.ndtv.com/delhi-news/coronavirus-delhi-civic-body-using-drones-to-check-temperature-of-people-on-balconies-2209832.
    [103] M. Abdel-Basset, V. Chang, N. A. Nabeeh, An intelligent framework using disruptive technologies for COVID-19 analysis, Technol. Forecast. Soc. Change, 163 (2021), 120431. doi: 10.1016/j.techfore.2020.120431
    [104] S. Gilgore, GWU hospital tackles COVID-19 with new testing site, telemedicine and outreach on D.C.'s east side, 2020.
    [105] M. Shah, A. Tosto, Industry voices—how rush university medical center's virtual investments became central to its COVID-19 response, 2020.
    [106] S. Simmons, R. Carrion, K. Alfson, H. Staples, C. Jinadatha, W. Jarvis, et al., Disinfection effect of pulsed xenon ultraviolet irradiation on SARS-CoV-2 and implications for environmental risk of COVID-19 transmission, medRxiv, 2020.
    [107] B. Spice, COVID-19 should be wake-up call for robotics research, 2020.
    [108] R. Vaishya, M. Javaid, I. H. Khan, A. Haleem, Artificial intelligence (AI) applications for COVID-19 pandemic, Diabetes Metab. Syndr. Clin. Res. Rev., 14 (2020), 337–339. doi: 10.1016/j.dsx.2020.04.012
    [109] B. G. Ahn, Y. H. Noh, D. U. Jeong, Smart chair based on multi heart rate detection system, in 2015 IEEE SENSORS, IEEE, (2015), 1–4.
    [110] I. Chiuchisan, H. N. Costin, O. Geman, Adopting the Internet of things technologies in health care systems, in 2014 International Conference and Exposition on Electrical and Power Engineering (EPE), IEEE, (2014), 532–535.
    [111] P. K. Sahoo, S. K. Mohapatra, S. L. Wu, Analyzing healthcare big data with prediction for future health condition, IEEE Access, 4 (2016), 9786–9799. doi: 10.1109/ACCESS.2016.2647619
    [112] G. Sharma, S. Kalra, A lightweight user authentication scheme for cloud-IoT based healthcare services, Iran. J. Sci. Technol. Trans. Electr. Eng., 43 (2019), 619–636.
    [113] F. Shi, J. Wang, J. Shi, Z. Wu, Q. Wang, Z. Tang, et al., Review of artificial intelligence techniques in imaging data acquisition, segmentation and diagnosis for COVID-19, IEEE Rev. Biomed. Eng., 2020.
    [114] L. Wang, Z. Q. Lin, A. Wong, COVID-net: atailored deep convolutional neural network design for detection of COVID-19 cases from chest x-ray images, Sci. Rep., 10 (2020), 1–12. doi: 10.1038/s41598-019-56847-4
    [115] M. Farooq, A. Hafeez, COVID-resnet: A deep learning framework for screening of COVID-19 from radiographs, preprint, arXiv: 2003.14395.
    [116] A. Roy, F. H. Kumbhar, H. S. Dhillon, N. Saxena, S. Y. Shin, S. Singh, Efficient monitoring and contact tracing for COVID-19: a smart iot-based framework, IEEE Internet Things Mag., 3 (2020), 17–23. doi: 10.1109/IOTM.0001.2000145
    [117] L. Wang, Microwave sensors for breast cancer detection, Sensors, 18 (2018), 655. doi: 10.3390/s18020655
    [118] T. C. Chiang, Y. S. Huang, R. T. Chen, C. S. Huang, R. F. Chang, Tumor detection in automated breast ultrasound using 3-d cnn and prioritized candidate aggregation, IEEE Trans. Med. Imaging, 38 (2018), 240–249.
    [119] Y. Lei, X. He, J. Yao, T. Wang, L. Wang, W. Li, et al., Breast tumor segmentation in 3d automatic breast ultrasound using mask scoring r-cnn, Med. Phys., 48 (2021), 204–214. doi: 10.1002/mp.14569
    [120] M. Veta, Y. J. Heng, N. Stathonikos, B. E. Bejnordi, F. Beca, T. Wollmann, et al., Predicting breast tumor proliferation from whole-slide images: the tupac16 challenge, Med. Image Anal., 54 (2019), 111–121. doi: 10.1016/j.media.2019.02.012
    [121] G. Pradhan, R. Pradhan, B. Khandelwal, A study on various machine learning algorithms used for prediction of diabetes mellitus, in Soft Computing Techniques and Applications, Springer, (2021), 553–561.
    [122] A. Shanthini, G. Manogaran, G. Vadivu, K. Kottilingam, P. Nithyakani, C. Fancy, Threshold segmentation based multi-layer analysis for detecting diabetic retinopathy using convolution neural network, J. Ambient Intell. Human. Comput., (2021), 1–15.
    [123] V. Bavkar, A. Shinde, Machine learning algorithms for diabetes prediction and neural network method for blood glucose measurement, Indian J. Sci. Technol., 14 (2021), 869–880. doi: 10.17485/IJST/v14i10.2187
    [124] E. Hussain, M. Hasan, M. A. Rahman, I. Lee, T. Tamanna, M. Z. Parvez, Corodet: a deep learning based classification for COVID-19 detection using chest x-ray images, Chaos Solitons Fractals, 142 (2021), 110495. doi: 10.1016/j.chaos.2020.110495
    [125] P. R. Bassi, R. Attux, A deep convolutional neural network for COVID-19 detection using chest x-rays, Res. Biomed. Eng., (2021), 1–10.
    [126] A. M. Ismael, A. Şengür, Deep learning approaches for COVID-19 detection based on chest x-ray images, Expert Syst. Appl., 164 (2021), 114054. doi: 10.1016/j.eswa.2020.114054
    [127] A. Tahamtan, A. Ardebili, Real-time rt-pcr in COVID-19 detection: issues affecting the results, Expert Rev. Mol. Diagn., 20 (2020), 453–454. doi: 10.1080/14737159.2020.1757437
    [128] B. Ghoshal, A. Tucker, Estimating uncertainty and interpretability in deep learning for coronavirus (COVID-19) detection, preprint, arXiv: 2003.10769.
    [129] A. Mangal, S. Kalia, H. Rajgopal, K. Rangarajan, V. Namboodiri, S. Banerjee, et al., Covidaid: COVID-19 detection using chest x-ray, preprint, arXiv: 2004.09803.
    [130] S. Vaid, R. Kalantar, M. Bhandari, Deep learning COVID-19 detection bias: accuracy through artificial intelligence, Int. Orthop., 44 (2020), 1539–1542. doi: 10.1007/s00264-020-04609-7
    [131] A. Waheed, M. Goyal, D. Gupta, A. Khanna, F. Al-Turjman, P. R. Pinheiro, Covidgan: data augmentation using auxiliary classifier gan for improved COVID-19 detection, IEEE Access, 8 (2020), 91 916–91 923. doi: 10.1109/ACCESS.2020.2994762
    [132] W. Liu, Q. Zhang, J. Chen, R. Xiang, H. Song, S. Shu, et al., Detection of COVID-19 in children in early january 2020 in Wuhan, China, N. Engl. J. Med., 382 (2020), 1370–1371. doi: 10.1056/NEJMc2003717
    [133] M. Z. Alom, M. Rahman, M. S. Nasrin, T. M. Taha, V. K. Asari, COVID_mtnet: COVID-19 detection with multi-task deep learning approaches, preprint, arXiv: 2004.03747.
    [134] L. Brunese, F. Mercaldo, A. Reginelli, A. Santone, Explainable deep learning for pulmonary disease and coronavirus COVID-19 detection from x-rays, Comput. Methods and Programs in Biomed., 196 (2020), 105608. doi: 10.1016/j.cmpb.2020.105608
    [135] L. Ni, F. Ye, M. L. Cheng, Y. Feng, Y. Q. Deng, H. Zhao, et al., Detection of SARS-CoV-2-specific humoral and cellular immunity in COVID-19 convalescent individuals, Immunity, 52 (2020), 971–977. doi: 10.1016/j.immuni.2020.04.023
    [136] A. Narin, C. Kaya, Z. Pamuk, Automatic detection of coronavirus disease (COVID-19) using x-ray images and deep convolutional neural networks, preprint, arXiv: 2003.10849.
    [137] T. Ozturk, M. Talo, E. A. Yildirim, U. B. Baloglu, O. Yildirim, U. R. Acharya, Automated detection of COVID-19 cases using deep neural networks with x-ray images, Comput. Biol. Med., 121 (2020), 103792. doi: 10.1016/j.compbiomed.2020.103792
    [138] P. K. Sethy, S. K. Behera, P. K. Ratha, P. Biswas, Detection of coronavirus disease (COVID-19) based on deep features and support vector machine, 2020.
    [139] A. Rahman, M. J. Islam, A. Montieri, M. K. Nasir, M. M. Reza, S. S. Band, et al., Smartblock-sdn: an optimized blockchain-sdn framework for resource management in IoT, IEEE Access, 9 (2021), 283 61–283 76. doi: 10.1109/ACCESS.2021.3096125
    [140] M. J. Islam, A. Rahman, S. Kabir, A. Khatun, A. Pritom, M. Chowdhury, Sdot-nfv: a distributed sdn based security system with IoT for smart city environments, GUB J. Sci. Eng., 7 (2021), 27–35.
    [141] M. Ndiaye, A. M. Abu-Mahfouz, G. P. Hancke, Sdnmm—a generic sdn-based modular management system for wireless sensor networks, IEEE Syst. J., 14 (2019), 2347–2357.
    [142] S. Islam, U. Sara, A. Kawsar, A. Rahman, D. Kundu, D. D. Dipta, et al., Sgbba: an efficient method for prediction system in machine learning using imbalance dataset, Int. J. Adv. Comput. Sci. Appl., 12 (2021).
    [143] A. Rahman, M. J. Islam, F. A. Sunny, M. K. Nasir, Distblocksdn: a distributed secure blockchain based sdn-IoT architecture with nfv implementation for smart cities, in 2019 2nd International Conference on Innovation in Engineering and Technology (ICIET), (2019), 1–6.
    [144] M. J. Hossain, M. A. H. Wadud, A. Rahman, J. Ferdous, M. F. Mridha, A secured patient's online data monitoring through blockchain: an intelligent way to store lifetime medical records, in International Conference on Science and Contemporary Technologies (ICSCT), 2021.
    [145] D. Li, 5G and intelligence medicine—how the next generation of wireless technology will reconstruct healthcare? Precis. Clin. Med., 2 (2019), 205–208.
    [146] Z. Allam, D. S. Jones, On the coronavirus (COVID-19) outbreak and the smart city network: universal data sharing standards coupled with artificial intelligence (AI) to benefit urban health monitoring and management, in Healthcare, Multidisciplinary Digital Publishing Institute, 8 (2020), 1–9.
  • Reader Comments
  • © 2021 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索
Mathematical Biosciences and Engineering
2.6 3.9

Metrics

Article views(4148) PDF downloads(177) Cited by(9)

Preview PDF
Download XML
Export Citation
Article outline

Figures and Tables

Figures(6)  /  Tables(4)

Other Articles By Authors

Related pages

Tools

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog