Cited by 335Blockchain Technology Applications and SecurityInternet of Things and AIIoT and Edge/Fog Computing

Application of Blockchain and Internet of Things in Healthcare and Medical Sector: Applications, Challenges, and Future Perspectives

Open access
Ratta, Pranav, Kaur, Amanpreet, Sharma, Sparsh, Shabaz, Mohammad, Dhiman, Gaurav·2021·Journal of Food Quality

Abstract

Internet of Things (IoT) is one of the recent innovations in Information Technology, which intends to interconnect the physical and digital worlds. It introduces a vision of smartness by enabling communication between objects and humans through the Internet. IoT has diverse applications in almost all sectors like Smart Health, Smart Transportation, and Smart Cities, etc. In healthcare applications, IoT eases communication between doctors and patients as the latter can be diagnosed remotely in emergency scenarios through body sensor networks and wearable sensors. However, using IoT in healthcare systems can lead to violation of the privacy of patients. Thus, security should be taken into consideration. Blockchain is one of the trending research topics nowadays and can be applied to the majority of IoT scenarios. Few major reasons for using the Blockchain in healthcare systems are its prominent features, i.e., Decentralization, Immutability, Security and Privacy, and Transparency. This paper’s main objective was to enhance the functionality of healthcare systems using emerging and innovative computer technologies like IoT and Blockchain. So, initially, a brief introduction to the basic concepts of IoT and Blockchain is provided. After this, the applicability of IoT and Blockchain in the medical sector is explored in three major areas—drug traceability, remote patient-monitoring, and medical record management. At last, the challenges of deploying IoT and Blockchain in healthcare systems are discussed.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1155/2021/7608296

Cites

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Peer assessment benefits include making the range of feedback wider and encouraging students to reflect, reducing marking load on teachers and increasing students' self-evaluation skills, and enhancing students' retention rate through motivation and reflection of their own learning.

    “Numerous benefits are observed such as (1) making the range feedback wider and encourages students to reflect, (2) reduces marking load on teachers, and increases students' selfevaluation skills [17,51], and (3) enhances students retention rate through motivation and reflection of their own learning [56].”

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

The citation lists haven’t been fetched yet

References 63 · Cited by 335

Research works printed but not linked: 5

  1. P. Gokhale, O. Bhat, and S. Bhat, "Introduction to IOT," International Advanced Research Journal in Science, Engi- neering and Technology, vol. 5, no. 1, pp. 41-44, 2018.
  2. D. Puthal, N. Malik, S. P. Mohanty, E. Kougianos, and C. Yang, " e blockchain as a decentralized security frame- work [future directions]," IEEE Consumer Electronics Mag- azine, vol. 7, no. 2, pp. 18-21, 2018.
  3. R. Duan, X. Chen, and T. Xing, "A QoS architecture for IOT," in Proceedings of the 2011 International Conference on Internet of ings and 4th International Conference on Cyber, Physical and Social Computing, IEEE, Liaoning, China, October 2011.
  4. S. Al-Sarawi, "Internet of things (IoT) communication pro- tocols," in Proceedings of the 2017 8th International Confer- ence on Information Technology (ICIT), IEEE, Amman, Jordan, May 2017.
  5. L. A. Linn and M. B. Koo, "Blockchain for health data and its potential use in health it and health care related research," in Proceedings of the ONC/NIST Use of Blockchain for Healthcare and Research Workshop, Gaithersburg, MA, USA, September 2016.

Authors
Ratta, P., Kaur, A., Sharma, S., Shabaz, M., & Dhiman, G.
Affiliations
  • Chandigarh University (IN)
  • National Institute of Technology Srinagar (IN)
  • Arba Minch University (ET)
  • Government Bikram College of Commerce, Patiala, Punjab, India
Corresponding author
Shabaz, Mohammad
Venue
Journal of Food Quality
Publisher
Wiley
Published
2021-05-25
Volume
2021
Pages
1-20
ISSN
  • 0146-9428 (ISSN-L)
  • 1745-4557
OpenAlex
W3165364558
Cited by
335
References
63
Citations by year
2026: 19 · 2025: 66 · 2024: 76 · 2023: 68 · 2022: 76 · 2021: 30
FWCI
56.41
Type
journal article
Language
en
Open access
Locations
  • Journal of Food Quality (publishedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Physical Sciences › Computer Science › Information Systems › Blockchain Technology Applications and Security
  • Physical Sciences › Computer Science › Information Systems › Internet of Things and AI
  • Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
Keywords
blockchain, Internet of Things, health care, drug traceability, remote patient monitoring, medical records management, patient privacy, Internet of Things security, wireless body area networks, wearable sensors, smart healthcare

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review