Skip to main content
SpringerLink
Log in

Blockchain Technologies for Internet of Medical Things (BIoMT) Based Healthcare Systems: A New Paradigm for COVID-19 Pandemic

  • Chapter
  • First Online:
Trends of Artificial Intelligence and Big Data for E-Health

Part of the book series: Integrated Science ((IS,volume 9))

Abstract

Blockchain and Internet of Medical Things (IOMT) technologies are becoming increasingly vital in the healthcare industry, with considerable growth predicted in the near future. Numerous blockchain-related applications have been developed and planned in the health sector. The decentralization, reliability, and transparency of data are all elements that place this technology as a revolution for industry, healthcare professionals and covid-19 patients. Connected devices generate and transmit data to improve patient outcomes, make workplaces and workflows more efficient, reduce medical errors, and enable buildings to meet the needs of those who occupy them better. Connected devices are sometimes excellent targets for hackers because of their capacity to access medical information in real time across various devices; thus, it is critical to protect the privacy of covid-19 patients. Thus, the contribution of the blockchain is more specifically related to health data. This technology addresses the issues of trust, security, and auditability of these data, thus complementing AI and IoT offerings based on similar data. In the realm of healthcare, the Internet of Things (IoT) has recently moved closer to the topic of blockchain, and new use cases combining these two technologies have emerged. In terms of the blockchain of IoMT (BIOMT), it would be feasible to take a significant step toward connected device autonomy while maintaining improved security: (1) data would not pass through a cloud but instead be sent directly to the service platform; (2) hacking entry points would be drastically reduced; (3) medical data would be dematerialized, saving time; and (4) the connected object could conduct medical transactions with complete security and transparency.

Blockchain in Healthcare Today (BHTY) is the world’s first peer review journal that amplifies and disseminates distributed ledger technology research and innovations in the healthcare sector. (Andrew Bosworth—Meta’s chief technology officer)

Those who design Internet of Medical Things devices are leading the charge into what has now become a digital health revolution. Smart, connected, and secure medical devices for telehealth, remote patient monitoring, and drug delivery compliance are completely changing the traditional healthcare delivery model. (Marten L. Smith Business Development Manager, Medical Products Group Microchip Technology, Inc.)

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 159.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Maksimovic M, Vujovic V, Perisic B (2015) A custom internet of things healthcare system

    Google Scholar 

  2. Cecil J, Cecil-Xavier A, Gupta A (2017) Foundational elements of next generation cyber physical and IoT frameworks for distributed collaboration. In: 2017 13th IEEE conference on automation science and engineering (CASE), pp 789–794

    Google Scholar 

  3. Dwivedi R, Mehrotra D, Chandra S (2021) Potential of internet of medical things (IoMT) applications in building a smart healthcare system: a systematic review. J Oral Biol Craniofacial Res. https://doi.org/10.1016/j.jobcr.2021.11.010

    Article  Google Scholar 

  4. Tarikere S, Donner I, Woods D (2021) Diagnosing a healthcare cybersecurity crisis: the impact of IoMT advancements and 5G. Bus Horiz 64:799–807. https://doi.org/10.1016/j.bushor.2021.07.015

    Article  Google Scholar 

  5. Ashfaq Z, Rafay A, Mumtaz R, Hassan Zaidi SM, Saleem H, Raza Zaidi SA, Mumtaz S, Haque A (2022) A review of enabling technologies for internet of medical things (IoMT) ecosystem. Ain Shams Eng J 13:101660. https://doi.org/10.1016/j.asej.2021.101660

    Article  Google Scholar 

  6. Pratap Singh R, Javaid M, Haleem A, Vaishya R, Ali S (2020) Internet of medical things (IoMT) for orthopaedic in COVID-19 pandemic: roles, challenges, and applications. J Clin Orthopaedics Trauma 11:713–717. https://doi.org/10.1016/j.jcot.2020.05.011

    Article  Google Scholar 

  7. Hajiheydari N, Delgosha MS, Olya H (2021) Scepticism and resistance to IoMT in healthcare: application of behavioural reasoning theory with configurational perspective. Technol Forecast Soc Chang 169:120807. https://doi.org/10.1016/j.techfore.2021.120807

    Article  Google Scholar 

  8. Peng J, Cai K, Jin X (2020) High concurrency massive data collection algorithm for IoMT applications. Comput Commun 157:402–409. https://doi.org/10.1016/j.comcom.2020.04.045

    Article  Google Scholar 

  9. Sridhar Raj S, Madiajagan M (2021) Chapter four—parallel machine learning and deep learning approaches for internet of medical things (IoMT). In: Sangaiah AK, Mukhopadhyay S (eds) Intelligent IoT systems in personalized health care. Academic Press, pp 89–103

    Google Scholar 

  10. Syed L, Jabeen S, Manimala S, Alsaeedi A (2019) Smart healthcare framework for ambient assisted living using IoMT and big data analytics techniques. Future Gener Comput Syst 101:136–151.https://doi.org/10.1016/j.future.2019.06.004

  11. Cecil J, Gupta A, Pirela-Cruz M, Ramanathan P (2018) An IoMT based cyber training framework for orthopedic surgery using next generation internet technologies. Inform Med Unlocked 12:128–137. https://doi.org/10.1016/j.imu.2018.05.002

    Article  Google Scholar 

  12. Mamun Q (2022) Blockchain technology in the future of healthcare. Smart Health 23:100223. https://doi.org/10.1016/j.smhl.2021.100223

    Article  Google Scholar 

  13. Massaro M (2021) Digital transformation in the healthcare sector through blockchain technology. Insights from academic research and business developments. Technovation 102386. https://doi.org/10.1016/j.technovation.2021.102386

  14. Hussien HM, Yasin SM, Udzir NI, Ninggal MIH, Salman S (2021) Blockchain technology in the healthcare industry: trends and opportunities. J Ind Inf Integr 22:100217. https://doi.org/10.1016/j.jii.2021.100217

    Article  Google Scholar 

  15. Haleem A, Javaid M, Singh RP, Suman R, Rab S (2021) Blockchain technology applications in healthcare: an overview. Int J Intell Netw 2:130–139. https://doi.org/10.1016/j.ijin.2021.09.005

    Article  Google Scholar 

  16. Sharma L, Olson J, Guha A, McDougal L (2021) How blockchain will transform the healthcare ecosystem. Bus Horiz 64:673–682. https://doi.org/10.1016/j.bushor.2021.02.019

    Article  Google Scholar 

  17. Saranya R, Murugan A (2021) A systematic review of enabling blockchain in healthcare system: analysis, current status, challenges and future direction. Mater Today Proc. https://doi.org/10.1016/j.matpr.2021.07.105

  18. Balasubramanian S, Shukla V, Sethi JS, Islam N, Saloum R (2021) A readiness assessment framework for blockchain adoption: a healthcare case study. Technol Forecast Soc Chang 165:120536. https://doi.org/10.1016/j.techfore.2020.120536

    Article  Google Scholar 

  19. Zhang G, Yang Z, Liu W (2021) Blockchain-based privacy preserving e-health system for healthcare data in cloud. Comput Netw 108586. https://doi.org/10.1016/j.comnet.2021.108586

  20. Soni M, Singh DK (2021) Blockchain-based security and privacy for biomedical and healthcare information exchange systems. Mater Today Proc. https://doi.org/10.1016/j.matpr.2021.02.094

  21. Rojas I, Valenzuela O, Rojas F, Herrera LJ, Ortuño FM (2020) Bioinformatics and biomedical engineering: 8th international work-conference, IWBBIO 2020, Granada, Spain, May 6–8, 2020, proceedings. Springer Nature

    Google Scholar 

  22. Nguyen DC, Nguyen KD, Pathirana PN (2019) A mobile cloud based IoMT framework for automated health assessment and management. In: 2019 41st annual international conference of the IEEE engineering in medicine and biology society (EMBC), pp 6517–6520

    Google Scholar 

  23. Yang T, Gentile M, Shen C-F, Cheng C-M (2020) Combining point-of-care diagnostics and internet of medical things (IoMT) to combat the COVID-19 pandemic. Diagnostics 10:224. https://doi.org/10.3390/diagnostics10040224

    Article  Google Scholar 

  24. Awotunde JB, Ogundokun RO, Misra S (2021) Cloud and IoMT-based big data analytics system during COVID-19 pandemic. In: Chakraborty C, Ghosh U, Ravi V, Shelke Y (eds) Efficient data handling for massive internet of medical things: healthcare data analytics. Springer International Publishing, Cham, pp 181–201

    Google Scholar 

  25. Sworna NS, Islam AKMM, Shatabda S, Islam S (2021) Towards development of IoT-ML driven healthcare systems: a survey. J Netw Comput Appl 196:103244. https://doi.org/10.1016/j.jnca.2021.103244

    Article  Google Scholar 

  26. Mohd Aman AH, Hassan WH, Sameen S, Attarbashi ZS, Alizadeh M, Latiff LA (2021) IoMT amid COVID-19 pandemic: application, architecture, technology, and security. J Netw Comput Appl 174:102886. https://doi.org/10.1016/j.jnca.2020.102886

    Article  Google Scholar 

  27. De Vito L, Picariello F, Tudosa I, Balestrieri E (2019) A novel method for compressed sensing based sampling of ECG signals in medical-IoT era

    Google Scholar 

  28. Rubí JNS, Gondim PRL (2019) IoMT platform for pervasive healthcare data aggregation, processing, and sharing based on OneM2M and OpenEHR. Sensors 19:4283.https://doi.org/10.3390/s19194283

  29. Bharati S, Podder P, Mondal MRH, Paul PK (2021) Applications and challenges of cloud integrated IoMT. In: Hassanien AE, Khamparia A, Gupta D, Shankar K, Slowik A (eds) Cognitive internet of medical things for smart healthcare: services and applications. Springer International Publishing, Cham, pp 67–85

    Chapter  Google Scholar 

  30. Husain S, Kunz A, Song J, Koshimizu T (2015) Interworking architecture between oneM2M service layer and underlying networks. In: 2014 IEEE Globecom workshops (GC Wkshps), 2014, pp 636–642.https://doi.org/10.1109/GLOCOMW.2014.7063504

  31. Mehmood I, Anwar S, Dilawar A, Zulfiqar I, Abbas R (2020) Managing data diversity on the internet of medical things (IoMT). Int J Inf Technol Comput Sci 12:49–56.https://doi.org/10.5815/ijitcs.2020.06.05

  32. Venkatesh DAN (2019) Reimagining the future of healthcare industry through internet of medical things (IoMT), artificial intelligence (AI), machine learning (ML), big data, mobile apps and advanced sensors. SSRN Electron J. https://doi.org/10.2139/ssrn.3522960

  33. Bansal A, Atri A (2021) IoT’s data processing using spark. In: The smart cyber ecosystem for sustainable development. Wiley, pp 91–109

    Google Scholar 

  34. Awotunde JB, Jimoh RG, Matiluko OE, Gbadamosi B, Ajamu GJ (2022) Artificial intelligence and an edge-IoMT-based system for combating COVID-19 pandemic. In: Tyagi AK, Abraham A, Kaklauskas A (eds) Intelligent interactive multimedia systems for e-healthcare applications. Springer, Singapore, pp 191–214

    Chapter  Google Scholar 

  35. Nazir A, Azhar A, Nazir U, Liu Y-F, WaqarS Q, Chen J-E, Alanazi E (2021) The rise of 3D printing entangled with smart computer aided design during COVID-19 era. J Manuf Syst 60:774–786. https://doi.org/10.1016/j.jmsy.2020.10.009

    Article  Google Scholar 

  36. Atanasov V, Sivkov Y (2020) Data fusion for IoMT in shiping. In: 2020 21st international symposium on electrical apparatus technologies (SIELA). pp 1–6

    Google Scholar 

  37. Rhbech A, Lotfi H, Bajit A, Barodi A, El Aidi S, Tamtaoui A (2020) An optimized and intelligent security-based message queuing protocol S-MQTT applied to medical IOT COVID-19 data monitoring platforms. In: 2020 international symposium on advanced electrical and communication technologies (ISAECT), pp 1–6

    Google Scholar 

  38. Sheeba Rani S, Selvakumar S, Pradeep Mohan Kumar K, Thanh Tai D, Dhiravida Chelvi E (2021) Internet of medical things (IoMT) with machine learning–based COVID-19 diagnosis model using chest X-ray images. In: Data science for COVID-19, pp 627–641. https://doi.org/10.1016/B978-0-12-824536-1.00001-0

  39. Khan MA, Algarni F (2020) A healthcare monitoring system for the diagnosis of heart disease in the IoMT cloud environment using MSSO-ANFIS. IEEE Access 8:122259–122269. https://doi.org/10.1109/ACCESS.2020.3006424

    Article  Google Scholar 

  40. Dai H-N, Wu Y, Wang H, Imran M, Haider N (2021) Blockchain-empowered edge intelligence for internet of medical things against COVID-19. IEEE Internet Things Mag 4:34–39. https://doi.org/10.1109/IOTM.0011.2100030

    Article  Google Scholar 

  41. Lin H, Garg S, Hu J, Wang X, Jalil Piran M, Hossain MS (2021) Privacy-enhanced data fusion for COVID-19 applications in intelligent internet of medical things. IEEE Internet Things J 8:15683–15693. https://doi.org/10.1109/JIOT.2020.3033129

    Article  Google Scholar 

  42. Ndiaye M, Oyewobi SS, Abu-Mahfouz AM, Hancke GP, Kurien AM, Djouani K (2020) IoT in the wake of COVID-19: a survey on contributions, challenges and evolution. IEEE Access 8:186821–186839. https://doi.org/10.1109/ACCESS.2020.3030090

    Article  Google Scholar 

  43. Rizk D, Rizk R, Hsu S (2019) Applied layered-security model to IoMT. In: 2019 IEEE international conference on intelligence and security informatics (ISI), pp 227–227

    Google Scholar 

  44. Mbunge E, Akinnuwesi B, Fashoto SG, Metfula AS, Mashwama P (2021) A critical review of emerging technologies for tackling COVID-19 pandemic. Human Behavior Emerg Technol 3:25–39. https://doi.org/10.1002/hbe2.237

    Article  Google Scholar 

  45. Masud M, Gaba GS, Alqahtani S, Muhammad G, Gupta BB, Kumar P, Ghoneim A (2021) A lightweight and robust secure key establishment protocol for internet of medical things in COVID-19 patients care. IEEE Internet Things J 8:15694–15703. https://doi.org/10.1109/JIOT.2020.3047662

    Article  Google Scholar 

  46. Zeng P, Zhang Z, Lu R, Choo K-KR (2021) Efficient policy-hiding and large universe attribute-based encryption with public traceability for internet of medical things. IEEE Internet Things J 8:10963–10972. https://doi.org/10.1109/JIOT.2021.3051362

    Article  Google Scholar 

  47. Rani S, Ahmed SH, Talwar R, Malhotra J, Song H (2017) IoMT: a reliable cross layer protocol for internet of multimedia things. IEEE Internet Things J 4:832–839. https://doi.org/10.1109/JIOT.2017.2671460

    Article  Google Scholar 

  48. Awotunde JB, Ajagbe SA, Idowu IR, Ndunagu JN (2021) An enhanced cloud-IoMT-based and machine learning for effective COVID-19 diagnosis system. In: Al-Turjman F, Nayyar A, Devi A, Shukla PK (eds) Intelligence of things: AI-IoT based critical-applications and innovations. Springer International Publishing, Cham, pp 55–76

    Chapter  Google Scholar 

  49. Tai Y, Gao B, Li Q, Yu Z, Zhu C, Chang V (2021) Trustworthy and intelligent COVID-19 diagnostic IoMT through XR and deep-learning-based clinic data access. IEEE Internet Things J 8:15965–15976. https://doi.org/10.1109/JIOT.2021.3055804

    Article  Google Scholar 

  50. Fourati LC, Rekhis S, Ayed S, Jmaiel M (2021) Connected medical kiosks to counter COVID-19: needs, architecture & design guidelines. In: 2021 international wireless communications and mobile computing (IWCMC), pp 2032–2037

    Google Scholar 

  51. Razdan S, Sharma S (2021) Internet of medical things (IoMT): overview, emerging technologies, and case studies. In: IETE technical review, pp 1–14.https://doi.org/10.1080/02564602.2021.1927863

  52. Dai H-N, Imran M, Haider N (2020) Blockchain-enabled internet of medical things to combat COVID-19. IEEE Internet Things Mag 3:52–57. https://doi.org/10.1109/IOTM.0001.2000087

    Article  Google Scholar 

  53. Das AK, Bera B, Giri D (2021) AI and blockchain-based cloud-assisted secure vaccine distribution and tracking in IoMT-enabled COVID-19 environment. IEEE Internet Things Mag 4:26–32. https://doi.org/10.1109/IOTM.0001.2100016

    Article  Google Scholar 

  54. Naren N, Chamola V, Baitragunta S, Chintanpalli A, Mishra P, Yenuganti S, Guizani M (2021) IoMT and DNN-enabled drone-assisted covid-19 screening and detection framework for rural areas. IEEE Internet Things Mag 4:4–9. https://doi.org/10.1109/IOTM.0011.2100053

    Article  Google Scholar 

  55. Ahmed I, Ahmad A, Jeon G (2021) An IoT-based deep learning framework for early assessment of covid-19. IEEE Internet Things J 8:15855–15862. https://doi.org/10.1109/JIOT.2020.3034074

    Article  Google Scholar 

  56. Rahman MdA, Hossain MS (2021) An internet-of-medical-things-enabled edge computing framework for tackling COVID-19. IEEE Internet Things J 8:15847–15854. https://doi.org/10.1109/JIOT.2021.3051080

    Article  Google Scholar 

  57. Abdel-Basset M, Chang V, Nabeeh NA (2021) An intelligent framework using disruptive technologies for COVID-19 analysis. Technol Forecast Soc Chang 163:120431. https://doi.org/10.1016/j.techfore.2020.120431

    Article  Google Scholar 

  58. Sarosh P, Parah SA, Bhat GM, Muhammad K (2021) A security management framework for big data in smart healthcare. Big Data Res 25:100225. https://doi.org/10.1016/j.bdr.2021.100225

    Article  Google Scholar 

  59. Nofer M, Gomber P, Hinz O, Schiereck D (2017) Blockchain. Bus Inf Syst Eng 59:183–187. https://doi.org/10.1007/s12599-017-0467-3

    Article  Google Scholar 

  60. Hasselgren A, Kralevska K, Gligoroski D, Pedersen SA, Faxvaag A (2020) Blockchain in healthcare and health sciences—a scoping review. Int J Med Inform 134:104040. https://doi.org/10.1016/j.ijmedinf.2019.104040

    Article  Google Scholar 

  61. De Aguiar EJ, Faiçal BS, Krishnamachari B, Ueyama J (2020) A survey of blockchain-based strategies for healthcare. ACM Comput Surv 53:1–27. https://doi.org/10.1145/3376915

  62. Khatoon A (2020) A blockchain-based smart contract system for healthcare management. Electronics 9:94. https://doi.org/10.3390/electronics9010094

    Article  Google Scholar 

  63. Griggs KN, Ossipova O, Kohlios CP, Baccarini AN, Howson EA, Hayajneh T (2018) Healthcare blockchain system using smart contracts for secure automated remote patient monitoring. J Med Syst 42:130. https://doi.org/10.1007/s10916-018-0982-x

    Article  Google Scholar 

  64. Zghaibeh M, Farooq U, Hasan NU, Baig I (2020) SHealth: a blockchain-based health system with smart contracts capabilities. IEEE Access 8:70030–70043. https://doi.org/10.1109/ACCESS.2020.2986789

    Article  Google Scholar 

  65. Novikov SP, Kazakov OD, Kulagina NA, Azarenko NY (2018) Blockchain and smart contracts in a decentralized health infrastructure. In: 2018 IEEE international conference “quality management, transport and information security, information technologies” (IT QM IS), pp 697–703

    Google Scholar 

  66. Dasaklis TK, Casino F, Patsakis C (2018) Blockchain meets smart health: towards next generation healthcare services. In: 2018 9th international conference on information, intelligence, systems and applications (IISA), pp 1–8

    Google Scholar 

  67. Pham HL, Tran TH, Nakashima Y (2018) A secure remote healthcare system for hospital using blockchain smart contract. In: 2018 IEEE Globecom workshops (GC Wkshps), pp 1–6

    Google Scholar 

  68. Shahnaz A, Qamar U, Khalid A (2019) Using blockchain for electronic health records. IEEE Access 7:147782–147795. https://doi.org/10.1109/ACCESS.2019.2946373

    Article  Google Scholar 

  69. Dubovitskaya A, Baig F, Xu Z, Shukla R, Zambani PS, Swaminathan A, Jahangir MM, Chowdhry K, Lachhani R, Idnani N, Schumacher M, Aberer K, Stoller SD, Ryu S, Wang F (2020) ACTION-EHR: patient-centric blockchain-based electronic health record data management for cancer care. J Med Internet Res 22:e13598. https://doi.org/10.2196/13598

    Article  Google Scholar 

  70. Tariq N, Qamar A, Asim M, Khan FA (2020) Blockchain and smart healthcare security: a survey. Proc Comput Sci 175:615–620. https://doi.org/10.1016/j.procs.2020.07.089

    Article  Google Scholar 

  71. Shi S, He D, Li L, Kumar N, Khan MK, Choo K-KR (2020) Applications of blockchain in ensuring the security and privacy of electronic health record systems: a survey. Comput Secur 97:101966. https://doi.org/10.1016/j.cose.2020.101966

    Article  Google Scholar 

  72. Zhuang Y, Sheets L, Shae Z, Tsai JJP, Shyu C-R (2018) Applying blockchain technology for health information exchange and persistent monitoring for clinical trials. AMIA Annu Symp Proc 2018:1167–1175

    Google Scholar 

  73. Fusco A, Dicuonzo G, Dell’Atti V, Tatullo M (2020) Blockchain in healthcare: insights on COVID-19. Int J Environ Res Public Health 17:E7167. https://doi.org/10.3390/ijerph17197167

    Article  CAS  Google Scholar 

  74. Christodoulou K, Christodoulou P, Zinonos Z, Carayannis EG, Chatzichristofis SA (2020) Health information exchange with blockchain amid covid-19-like pandemics. In: 2020 16th international conference on distributed computing in sensor systems (DCOSS), pp 412–417

    Google Scholar 

  75. Li X, Tao B, Dai H-N, Imran M, Wan D, Li D (2021) Is blockchain for internet of medical things a panacea for COVID-19 pandemic? Pervasive Mob Comput 75:101434. https://doi.org/10.1016/j.pmcj.2021.101434

    Article  Google Scholar 

  76. Udgata SK, Suryadevara NK (2021) COVID-19, sensors, and internet of medical things (IoMT). In: Udgata SK, Suryadevara NK (eds) Internet of things and sensor network for COVID-19. Springer, Singapore, pp 39–53

    Chapter  Google Scholar 

  77. Kumar M, Rani R (2021) SAI-BA-IoMT: secure AI-based blockchain-assisted internet of medical things tool to moderate the outbreak of COVID-19 crisis. arXiv:210809539 [cs]

  78. Mareiniss DP (2020) The impending storm: COVID-19, pandemics and our overwhelmed emergency departments. Am J Emerg Med 38:1293–1294. https://doi.org/10.1016/j.ajem.2020.03.033

    Article  Google Scholar 

  79. Tan L, Yu K, Shi N, Yang C, Wei W, Lu H (2021) Towards secure and privacy-preserving data sharing for COVID-19 medical records: a blockchain-empowered approach. IEEE Trans Netw Sci Eng:1–1.https://doi.org/10.1109/TNSE.2021.3101842

  80. Theodos K, Sittig S (2020) Health information privacy laws in the digital age: HIPAA doesn’t apply. Perspect Health Inf Manage 18:1l

    Google Scholar 

  81. Sajid A (2020) A taxonomy of cyber-attacks on computer networks. University of Bradford

    Google Scholar 

  82. Jolley D, Paterson JL (2020) Pylons ablaze: examining the role of 5G COVID-19 conspiracy beliefs and support for violence. Br J Soc Psychol 59:628–640. https://doi.org/10.1111/bjso.12394

    Article  Google Scholar 

  83. Siriwardhana Y, Gür G, Ylianttila M, Liyanage M (2021) The role of 5G for digital healthcare against COVID-19 pandemic: opportunities and challenges. ICT Express 7:244–252. https://doi.org/10.1016/j.icte.2020.10.002

    Article  Google Scholar 

  84. Sittig DF, Singh H (2020) COVID-19 and the need for a national health information technology infrastructure. JAMA 323:2373–2374. https://doi.org/10.1001/jama.2020.7239

    Article  CAS  Google Scholar 

  85. Vyas A, Sundara Raman R, Ceccio N, Lutscher PM, Ensafi R (2021) Lost in transmission: investigating filtering of COVID-19 websites. In: Borisov N, Diaz C (eds) Financial cryptography and data security. Springer, Berlin, Heidelberg, pp 417–436

    Chapter  Google Scholar 

  86. Al-Kuraishy HM, Al-Gareeb AI, Qusti S, Alshammari EM, Gyebi GA, Batiha GE (2021) Covid-19-induced dysautonomia: a menace of sympathetic storm. ASN Neuro 13:17590914211057636. https://doi.org/10.1177/17590914211057635

  87. Jung Y, Agulto R (2021) A public platform for virtual IoT-based monitoring and tracking of COVID-19. Electronics 10:12. https://doi.org/10.3390/electronics10010012

    Article  CAS  Google Scholar 

  88. Xia P, Nabeel M, Khalil I, Wang H, Yu T (2021) Identifying and characterizing COVID-19 themed malicious domain campaigns. In: Proceedings of the eleventh ACM conference on data and application security and privacy. Association for Computing Machinery, New York, NY, USA, pp 209–220

    Google Scholar 

  89. Qi R, Feng C, Liu Z, Mrad N (2017) Blockchain-powered internet of things, E-governance and E-democracy. In: Vinod Kumar TM (ed) E-democracy for smart cities. Springer, Singapore, pp 509–520

    Chapter  Google Scholar 

  90. Shah H, Shah M, Tanwar S, Kumar N (2021) Blockchain for COVID-19: a comprehensive review. Pers Ubiquit Comput. https://doi.org/10.1007/s00779-021-01610-8

    Article  Google Scholar 

  91. Marbouh D, Abbasi T, Maasmi F, Omar IA, Debe MS, Salah K, Jayaraman R, Ellahham S (2020) Blockchain for COVID-19: review, opportunities, and a trusted tracking system. Arab J Sci Eng 45:9895–9911. https://doi.org/10.1007/s13369-020-04950-4

    Article  CAS  Google Scholar 

  92. Ltd I-IB (2020) COVID-19 response and recovery in smart sustainable city governance and management: data-driven internet of things systems and machine learning-based analytics. Geopolit Hist Int Relat 12:16–22

    Article  Google Scholar 

  93. Nagori V (2021) “Aarogya Setu”: the mobile application that monitors and mitigates the risks of COVID-19 pandemic spread in India. J Inf Technol Teach Cases 11:66–80. https://doi.org/10.1177/2043886920985863

    Article  Google Scholar 

  94. Dąbrowska-Kłosińska P, Grzelak A, Nimark A (2021) The use of covid-19 digital applications and unavoidable threats to the protection of health data and privacy. Białostockie Studia Prawnicze 26:61–94. https://doi.org/10.15290/bsp.2021.26.03.04

  95. Binkheder S, Aldekhyyel RN, AlMogbel A, Al-Twairesh N, Alhumaid N, Aldekhyyel SN, Jamal AA (2021) Public perceptions around mHealth applications during COVID-19 pandemic: a network and sentiment analysis of tweets in Saudi Arabia. Int J Environ Res Public Health 18:13388. https://doi.org/10.3390/ijerph182413388

    Article  CAS  Google Scholar 

  96. Stevens H, Haines MB (2020) TraceTogether: pandemic response, democracy, and technology. https://doi.org/10.1215/18752160-8698301

  97. Verma J, Mishra AS (2020) COVID-19 infection: disease detection and mobile technology. PeerJ 8:e10345. https://doi.org/10.7717/peerj.10345

    Article  CAS  Google Scholar 

  98. Wang D, Liu F (2020) Privacy risk and preservation for COVID-19 contact tracing apps. arXiv:200615433 [cs]

  99. Tedeschi P, Bakiras S, Di Pietro R (2021) IoTrace: a flexible, efficient, and privacy-preserving IoT-enabled architecture for contact tracing. IEEE Commun Mag 59:82–88. https://doi.org/10.1109/MCOM.001.2000729

    Article  Google Scholar 

  100. Lochlainn MN, Lee KA, Sudre CH, Varsavsky T, Cardoso MJ, Menni C, Bowyer RCE, Nguyen LH, Drew DA, Ganesh S, Cadet JL du, Visconti A, Freidin MB, Modat M, Graham MS, Pujol JC, Murray B, Moustafa JSE-S, Zhang X, Davies R, Falchi M, Wolf J, Spector TD, Chan AT, Ourselin S, Steves CJ, COPE Consortium (2020) Key predictors of attending hospital with COVID19: an association study from the COVID symptom tracker app in 2,618,948 individuals

    Google Scholar 

  101. Zens M, Brammertz A, Herpich J, Südkamp N, Hinterseer M (2020) App-based tracking of self-reported COVID-19 symptoms: analysis of questionnaire data. J Med Internet Res 22:e21956. https://doi.org/10.2196/21956

    Article  Google Scholar 

  102. Ocheja P, Cao Y, Ding S, Yoshikawa M (2020) Quantifying the privacy-utility trade-offs in COVID-19 contact tracing apps. arXiv:201213061 [cs]

  103. Torky M, Hassanien AE (2020) COVID-19 blockchain framework: innovative approach. arXiv:200406081 [cs]

  104. Alam T (2020) Internet of things and blockchain-based framework for coronavirus (COVID-19) disease. Social Science Research Network, Rochester, NY

    Google Scholar 

  105. Humayun M (2020) Blockchain-based secure framework for e-learning during COVID-19. INDJST 13:1328–1341. https://doi.org/10.17485/IJST/v13i12.152

  106. Choudhury H, Goswami B, Gurung SK (2021) CovidChain: an anonymity preserving blockchain based framework for protection against covid-19. Inf Secur J Glob Perspect 30:257–280. https://doi.org/10.1080/19393555.2021.1921315

    Article  Google Scholar 

  107. Song J, Gu T, Fang Z, Feng X, Ge Y, Fu H, Hu P, Mohapatra P (2021) Blockchain meets COVID-19: a framework for contact information sharing and risk notification system. In: 2021 IEEE 18th international conference on mobile ad hoc and smart systems (MASS), pp 269–277

    Google Scholar 

  108. Angelopoulos CM, Damianou A, Katos V (2005) DHP framework: digital health passports using blockchain—use case on international tourism during the COVID-19 pandemic. Mon Not R Astron Soc 359:567–579. https://doi.org/10.1111/j.1365-2966.2005.08922.x

    Article  Google Scholar 

  109. Alsamhi SH, Lee B (2020) Blockchain for multi-robot collaboration to combat COVID-19 and future pandemics. arXiv:201002137 [cs, eess]

  110. Aslam B, Javed AR, Chakraborty C, Nebhen J, Raqib S, Rizwan M (2021) Blockchain and ANFIS empowered IoMT application for privacy preserved contact tracing in COVID-19 pandemic. Pers Ubiquit Comput. https://doi.org/10.1007/s00779-021-01596-3

    Article  Google Scholar 

  111. Muhammad G, Hossain MS (2021) A deep-learning-based edge-centric COVID-19-like pandemic screening and diagnosis system within a B5G framework using blockchain. IEEE Netw 35:74–81. https://doi.org/10.1109/MNET.011.2000326

    Article  Google Scholar 

  112. Alabdulkarim Y, Alameer A, Almukaynizi M, Almaslukh A (2021) SPIN: a blockchain-based framework for sharing COVID-19 pandemic information across nations. Appl Sci 11:8767. https://doi.org/10.3390/app11188767

    Article  CAS  Google Scholar 

  113. Omar I, Debe M, Jayaraman R, Salah K, Omar M, Arshad J (2020) Blockchain-based supply chain traceability for COVID-19 PPE. https://doi.org/10.36227/techrxiv.13227623.v1

Download references

Author information

Authors and Affiliations

  1. COSMOS Laboratory, National School of Computer Sciences (ENSI), University of Manouba, Manouba, Tunisia

    Houneida Sakly

  2. Radiology and Medical Imaging Unit, International Center Carthage Medical, Monastir, Tunisia

    Mourad Said

  3. University of California, San Francisco, Berkeley, USA

    Ahmed A. Al-Sayed

  4. Higher School of Health Sciences and Techniques, Monastir, Tunisia

    Chawki Loussaief & Rachid Sakly

  5. Department of Radiology, Stanford University School of Medicine, Palo Alto, USA

    Jayne Seekins

Authors
  1. Houneida Sakly
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mourad Said
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ahmed A. Al-Sayed
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Chawki Loussaief
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Rachid Sakly
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Jayne Seekins
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Houneida Sakly .

Editor information

Editors and Affiliations

  1. National School of Computer Science (ENSI), Manouba University, COSMOS Laboratory, Manouba, Tunisia

    Houneida Sakly

  2. Department of Radiology, Stanford University, Palo Alto, CA, USA

    Kristen Yeom

  3. Northwestern University, Chicago, IL, USA

    Safwan Halabi

  4. Radiologist and Associate Professor in medical Imaging, Carthage Medical International Center Monastir and Sousse Medina Medical Imaging Center, Monastir, Tunisia

    Mourad Said

  5. Department Radiology, Stanford Medicine, Palo Alto, CA, USA

    Jayne Seekins

  6. National School of Computer Science (ENSI), Manouba University, COSMOS Laboratory, Manouba, Tunisia

    Moncef Tagina

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Sakly, H., Said, M., Al-Sayed, A.A., Loussaief, C., Sakly, R., Seekins, J. (2022). Blockchain Technologies for Internet of Medical Things (BIoMT) Based Healthcare Systems: A New Paradigm for COVID-19 Pandemic. In: Sakly, H., Yeom, K., Halabi, S., Said, M., Seekins, J., Tagina, M. (eds) Trends of Artificial Intelligence and Big Data for E-Health. Integrated Science, vol 9. Springer, Cham. https://doi.org/10.1007/978-3-031-11199-0_8

Download citation

Publish with us

Policies and ethics

Search

Navigation