Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 840

The DOI matches its Crossref record; 22 of the 22 references it cites were found in a registry or an index.

The Future of Healthcare Internet of Things: A Survey of Emerging Technologies

Qadri, Yazdan Ahmad, Nauman, Ali, Zikria, Yousaf Bin, Vasilakos, Athanasios V., Kim, Sung Won·2020·IEEE Communications Surveys & Tutorials

Abstract

The impact of the Internet of Things (IoT) on the advancement of the healthcare industry is immense. The ushering of the Medicine 4.0 has resulted in an increased effort to develop platforms, both at the hardware level as well as the underlying software level. This vision has led to the development of Healthcare IoT (H-IoT) systems. The basic enabling technologies include the communication systems between the sensing nodes and the processors; and the processing algorithms for generating an output from the data collected by the sensors. However, at present, these enabling technologies are also supported by several new technologies. The use of Artificial Intelligence (AI) has transformed the H-IoT systems at almost every level. The fog/edge paradigm is bringing the computing power close to the deployed network and hence mitigating many challenges in the process. While the big data allows handling an enormous amount of data. Additionally, the Software Defined Networks (SDNs) bring flexibility to the system while the blockchains are finding the most novel use cases in H-IoT systems. The Internet of Nano Things (IoNT) and Tactile Internet (TI) are driving the innovation in the H-IoT applications. This paper delves into the ways these technologies are transforming the H-IoT systems and also identifies the future course for improving the Quality of Service (QoS) using these new technologies.

Overview

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 · 10.1109/comst.2020.2973314

Cites

22 of 22 references verified0 citation errors · 0 not checkable

Statistics

Verification

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

Self-check

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

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

Citations

Cites

Show all 22 references

Research works printed but not linked: 237

  1. 10.1109/ACCESS.2016.2638449 · DOI
  2. kumar, 2016, Big data analytics of IoT based health care monitoring system, Proc IEEE Uttar Pradesh Section Int Conf Elect Comput Electron Eng (UPCON), 55
  3. 10.1109/CBI.2017.3 · DOI
  4. 10.1109/PlatCon.2019.8669432 · DOI
  5. 10.1109/AINA.2016.158 · DOI · Paper page
  6. 10.1109/ACCESS.2016.2626316 · DOI
  7. 10.1109/BigDataService.2016.18 · DOI
  8. 10.1109/ACCESS.2017.2719921 · DOI · Paper page
  9. 10.1109/ACCESS.2018.2849822 · DOI
  10. 10.4258/hir.2016.22.3.156 · DOI · Paper page
  11. 10.1007/s11277-016-3842-3 · DOI
  12. 10.1109/INTELSE.2016.7475151 · DOI · Paper page
  13. 10.1109/MITP.2016.42 · DOI · Paper page
  14. 10.1007/978-3-319-57348-9_16 · DOI
  15. 2018, Wearables Sales Revenue Worldwide 2015–2021—Statistic
  16. 10.1109/SM2C.2017.8071260 · doi:10.1109/sm2c.2017.8071260
  17. 10.1016/j.jii.2016.03.004 · DOI · Paper page
  18. 10.1109/JSYST.2016.2558449 · DOI
  19. 10.1109/MCOM.2018.1700788 · DOI · Paper page
  20. 10.1016/j.ins.2015.05.040 · DOI
  21. 10.1109/ACCESS.2018.2817615 · DOI · Paper page
  22. 10.1109/MCOM.2018.1700364 · DOI · Paper page
  23. 10.1016/j.ins.2018.02.005 · DOI · Paper page
  24. 10.1109/JIOT.2018.2882794 · DOI · Paper page
  25. nakamoto, 2008, Bitcoin A Peer-to-Peer Electronic Cash System
  26. 10.1186/s13635-019-0085-3 · DOI
  27. 10.1016/j.jnca.2018.02.008 · DOI · Paper page
  28. 10.1016/j.pmcj.2017.06.018 · DOI · Paper page
  29. 10.1109/ACCESS.2016.2647619 · DOI · Paper page
  30. 10.1016/j.comnet.2019.03.006 · DOI · Paper page
  31. 10.1109/ACCESS.2015.2437951 · DOI · Paper page
  32. 10.1109/JSEN.2017.2786301 · DOI
  33. 10.1016/j.future.2018.07.049 · DOI · Paper page
  34. 10.1109/RBME.2017.2738009 · DOI
  35. 10.1109/COMST.2017.2731979 · DOI · Paper page
  36. 10.1109/ISCO.2017.7856042 · DOI
  37. 10.1109/ICIIECS.2017.8276162 · DOI
  38. 10.1155/2018/5978636 · DOI · Paper page
  39. 10.1016/j.jisa.2014.04.001 · DOI
  40. 10.1109/SmartIoT.2018.00038 · DOI
  41. 10.1145/3278576.3278597 · DOI
  42. 10.1080/02564602.2017.1406828 · DOI
  43. 10.1016/j.future.2018.04.024 · DOI
  44. 10.1109/ICIAS.2018.8540606 · DOI
  45. ramalho, 2015, Enhancing e-Health smart applications: A fog-enable, Proc 17th HealthCom, 323
  46. siddique, 2018, Approxcs Near-sensor approximate compressed sensing for iot-healthcare systems
  47. 10.1109/HealthCom.2017.8210825 · DOI
  48. 10.1109/LISAT.2018.8378012 · doi:10.1109/lisat.2018.8378012
  49. 10.1007/s12083-018-0705-6 · DOI
  50. 10.1109/DASC/PiCom/DataCom/CyberSciTec.2018.00092 · doi:10.1109/dasc/picom/datacom/cyberscitec.2018.00092
  51. 10.1016/j.compeleceng.2018.08.021 · DOI · Paper page
  52. al-odat, 2018, IoT-based secure embedded scheme for insulin pump data acquisition and monitoring
  53. 10.1109/MC.2017.201 · DOI · Paper page
  54. 10.1109/RTEICT.2017.8256654 · DOI
  55. 10.1109/SURV.2011.061710.00109 · DOI
  56. 10.1007/978-3-030-01560-2_6 · DOI
  57. 10.4018/978-1-5225-7952-6.ch010 · DOI
  58. 10.1109/ACCESS.2020.2964280 · DOI · Paper page
  59. 10.1016/j.future.2017.09.016 · DOI · Paper page
  60. 10.3389/fict.2018.00030 · DOI
  61. palanisamy, 2017, Implications of big data analytics in developing healthcare frameworks—A review, J King Saud Univ -Comput Inf Sci, 31, 415
  62. 10.2196/medinform.5359 · DOI · Paper page
  63. 10.1109/COMST.2018.2844341 · DOI · Paper page
  64. 10.1109/COMST.2017.2694469 · DOI · Paper page
  65. qiu, 2018, A survey on smart wearables in the application of fitness, Proc IEEE 15th Int Conf Depend Auton Secure Comput 15th Int Conf Pervasive Intell Comput 3rd Int Conf Big Data Intell Comput Cyber Sci Technol Congr DASC Pi Com/Data Com/Cyber Sci, 303
  66. 10.1109/CCNC.2017.7983083 · doi:10.1109/ccnc.2017.7983083
  67. 10.1155/2015/213705 · DOI
  68. 2018, Global Wearables Market Grows 7 7% in 4Q17 and 10 3% in 2017 as Apple Seizes the Leader Position Says IDC
  69. 10.1016/j.future.2017.04.036 · DOI · Paper page
  70. 10.1109/COMST.2018.2846401 · DOI · Paper page
  71. 10.1002/adma.201801511 · DOI · Paper page
  72. 10.1109/ACCESS.2018.2846609 · DOI · Paper page
  73. 10.1016/j.future.2017.10.045 · DOI · Paper page
  74. 10.1109/ACCESS.2018.2845399 · DOI
  75. 10.3390/s19081793 · DOI
  76. 10.1007/s10544-019-0377-x · DOI
  77. 10.23919/URSI-AT-RASC.2018.8471421 · DOI
  78. 10.1109/ACCESS.2018.2808324 · DOI · Paper page
  79. zhang, 2019, Thirty years of machine learning The road to Pareto-optimal next-generation wireless networks
  80. singh, 2016, An IoT framework for healthcare monitoring systems, Int J Comput Sci Inf Security, 14, 451
  81. 10.1109/TWC.2019.2901850 · DOI
  82. 10.1016/j.future.2018.04.036 · DOI · Paper page
  83. 10.1109/ICICET.2018.8533869 · doi:10.1109/icicet.2018.8533869
  84. 10.1109/ACCESS.2019.2890895 · DOI
  85. 10.1109/MCOM.2017.1600374CM · DOI · Paper page
  86. 10.1109/ICCE-Berlin.2017.8210598 · doi:10.1109/icce-berlin.2017.8210598
  87. 10.1109/TBDATA.2017.2769670 · DOI · Paper page
  88. 10.1109/ICBSII.2018.8524816 · doi:10.1109/icbsii.2018.8524816
  89. 10.1109/GLOCOM.2018.8647660 · doi:10.1109/glocom.2018.8647660
  90. 10.1109/JTEHM.2018.2861882 · DOI
  91. šatala, 2018, Using IoT devices for movement detection in medical environment—Proof of concept, Proc IEEE 16th World Symp Appl Mach Intell Informatics (SAMI), 61
  92. baby, 2018, Parkinson’s disease assist device using machine learning and Internet of Things, Proc Int Conf Commun Signal Process (ICCSP), 922
  93. 10.1109/COMST.2018.2862350 · DOI · Paper page
  94. 10.3390/jsan6040026 · DOI
  95. 10.1109/MCOM.2018.1700707 · DOI · Paper page
  96. 10.1109/MCOM.2018.1701177 · DOI
  97. 10.1109/ACCESS.2018.2886216 · DOI · Paper page
  98. 10.1186/s13638-016-0659-4 · doi:10.1186/s13638-016-0659-4
  99. 10.1016/j.comnet.2018.07.020 · DOI · Paper page
  100. 2019, About Cardiovascular Diseases
  101. 10.1109/SCOReD.2012.6518609 · doi:10.1109/scored.2012.6518609
  102. 10.1109/ACCESS.2017.2730843 · DOI · Paper page
  103. 10.1016/j.future.2013.01.010 · DOI · Paper page
  104. 10.1109/MCOM.2013.6461195 · DOI · Paper page
  105. 10.1109/ACCESS.2018.2846779 · DOI · Paper page
  106. simic, 2017, (PDF) A Case Study IoT and Blockchain Powered Healthcare
  107. 10.1109/ACCESS.2016.2645904 · DOI · Paper page
  108. taulli, 2019, Cool AI Highlights at CES Forbes
  109. 10.1109/PIMRC.2016.7794563 · DOI
  110. 10.1016/bs.adcom.2018.10.006 · DOI
  111. 10.1109/ICCSP.2017.8286475 · DOI
  112. 10.3390/s18082575 · DOI · Paper page
  113. 10.1109/IWCMC.2018.8450275 · DOI
  114. 10.1109/COMST.2019.2899617 · DOI · Paper page
  115. 10.1109/ICSCET.2018.8537314 · doi:10.1109/icscet.2018.8537314
  116. 10.4258/hir.2017.23.1.4 · DOI · Paper page
  117. 10.1109/ICTKE.2017.8259629 · DOI · Paper page
  118. ahmed, 2018, Applying Internet of Things and machine-learning for personalized healthcare: Issues and challenges, Proc Int Conf Mach Learn Data Eng (iCMLDE), 19, 10.1109/iCMLDE.2018.00014 · DOI
  119. bell, 2019, The Best Health Tech and Fitness Innovations at CES 2019 Forbes
  120. 10.3390/inventions4010008 · DOI
  121. 10.1109/EMBC.2019.8857832 · DOI
  122. 10.1109/MIC.2018.112102418 · DOI
  123. 10.1109/CyberC.2017.83 · DOI
  124. 2017, Health at a Glance 2017 OECD Indicators
  125. alvarez, 2017, Multimodal monitoring of Parkinson’s and Alzheimer’s patients using the ICT4LIFE platform, Proc IEEE Int Conf Adv Video Signal Surveill (AVSS), 1
  126. 10.1016/j.jisa.2019.02.002 · DOI
  127. 10.1109/JEC-ECC.2017.8305801 · DOI
  128. mulero, 2017, An AAL system based on IoT technologies and linked open data for elderly monitoring in smart cities, Proc 2nd Int Multidiscipl Conf Comput Energy Sci (SpliTech), 1
  129. almeida, 2018, A performance analysis of an IoT-aware elderly monitoring system, Proc 3rd Int Conf Smart Sustain Technol (SpliTech), 1
  130. 10.1109/ISSI.2018.8538186 · doi:10.1109/issi.2018.8538186
  131. 10.1109/MNET.2015.7113223 · DOI
  132. 10.1109/ITECHA.2017.8101902 · DOI
  133. el-saadany, 2017, A wireless early prediction system of cardiac arrest through IoT, Proc IEEE 41st Annu Comput Softw Appl Conf (COMPSAC), 690
  134. 10.1109/ISNCC.2018.8530920 · DOI
  135. 10.1109/JSYST.2016.2615761 · DOI · Paper page
  136. 10.1109/GLOCOM.2016.7841889 · DOI
  137. 10.1109/ICOIN.2017.7899572 · doi:10.1109/icoin.2017.7899572
  138. 10.1109/LCNW.2015.7365931 · DOI
  139. 10.1109/JCN.2017.000094 · DOI
  140. 10.1109/COMST.2015.2402617 · DOI
  141. 10.1007/s11036-016-0676-x · DOI · Paper page
  142. hasan, 2019, A novel framework for software defined wireless body area network, Proc 8th Int Conf Intell Syst Model Simulat, 1
  143. 10.1109/WAINA.2016.52 · DOI
  144. 10.1109/HealthCom.2017.8210833 · doi:10.1109/healthcom.2017.8210833
  145. 10.1109/TENCONSpring.2016.7519425 · DOI
  146. 10.1109/WOCC.2018.8372689 · DOI
  147. 10.1109/ICCEREC.2016.7814973 · doi:10.1109/iccerec.2016.7814973
  148. 10.1109/TNSM.2018.2815280 · DOI
  149. 10.1109/I2CT.2017.8226154 · DOI
  150. 10.1146/annurev-anchem-061417-125956 · DOI · Paper page
  151. 10.1109/JPROC.2019.2917625 · DOI
  152. 10.1109/JPROC.2019.2927926 · DOI
  153. 10.1109/JPROC.2019.2919455 · DOI · Paper page
  154. 10.1109/IWCMC.2016.7577059 · DOI
  155. 10.1109/TNB.2019.2957244 · doi:10.1109/tnb.2019.2957244
  156. 10.1109/TNB.2017.2762160 · DOI
  157. 10.1109/LNET.2019.2943692 · DOI
  158. 10.1109/ACCESS.2017.2677498 · DOI
  159. 10.1177/026119290803600610 · DOI
  160. 10.1109/JPROC.2019.2913890 · doi:10.1109/jproc.2019.2913890
  161. 10.1109/JPROC.2019.2916081 · DOI · Paper page
  162. 10.1109/WF-IoT.2018.8355116 · DOI
  163. 10.1109/ACCESS.2018.2869702 · DOI
  164. 10.1109/ISIE.2016.7745049 · doi:10.1109/isie.2016.7745049
  165. 10.1016/j.cose.2011.08.009 · DOI · Paper page
  166. 10.1109/LCOMM.2014.2364226 · doi:10.1109/lcomm.2014.2364226
  167. 10.1109/JSEN.2017.2752286 · doi:10.1109/jsen.2017.2752286
  168. 10.1109/APWiMob.2016.7811445 · DOI
  169. ghate, 2018, Machine learning for data aggregation in WSN: A survey, Int J Pure Appl Math, 118, 1
  170. 10.1177/1550147718768994 · DOI · Paper page
  171. 10.1109/SC2.2017.18 · doi:10.1109/sc2.2017.18
  172. 10.1007/s11036-017-0940-8 · doi:10.1007/s11036-017-0940-8
  173. 10.4108/icst.simutools.2013.251699 · DOI
  174. 10.1109/MC.2012.389 · DOI · Paper page
  175. 10.1145/2800795.2800809 · doi:10.1145/2800795.2800809
  176. 10.1109/MCOM.2016.7470948 · DOI · Paper page
  177. mohrehkesh, 2014, RIH-MAC: Receiver-initiated harvesting-aware MAC for nanoNetworks, Proc ACM 1st Annu Int Conf Nanoscale Comput Commun (NANOCOM), 1
  178. 10.1109/JIOT.2016.2573679 · doi:10.1109/jiot.2016.2573679
  179. 10.1109/ACCESS.2018.2859340 · DOI
  180. 10.1109/JIOT.2019.2907046 · DOI
  181. 10.1016/j.dcan.2017.07.001 · DOI · Paper page
  182. tanganelli, 2017, Ensuring quality of service in the Internet of Things, New Advances in the Internet of Things Studies in Computational Intelligence, 139
  183. 2015, Cisco Fog Computing Solutions Unleash the Power of the Internet of Things White Paper
  184. luan, 2015, Fog Computing Focusing on Mobile Users at the Edge
  185. 10.1109/MCOM.2017.7901470 · DOI · Paper page
  186. 10.3390/s19010021 · DOI · Paper page
  187. 10.1177/1687814018819515 · DOI
  188. minerva, 2015, Towards a Definition of the Internet of Things (IoT)
  189. 10.1109/TII.2018.2843169 · DOI · Paper page
  190. 2018, The Internet of Things How to capture the value of IoT
  191. 10.1109/EuCNC.2017.7980645 · DOI
  192. 10.1109/MWC.2016.1500157RP · DOI · Paper page
  193. fettweis, 2014, The Tactile Internet ITU-T Technology Watch Report
  194. 10.1038/s41591-019-0366-x · DOI · Paper page
  195. simsek, 2016, The 5G-enabled Tactile Internet: Applications, requirements, and architecture, Proc IEEE Wireless Commun Netw Conf, 61
  196. 10.3390/jsan7010001 · DOI
  197. 10.1109/JPROC.2018.2864587 · DOI
  198. 10.1109/JSEN.2019.2907664 · DOI
  199. 10.1109/MITE.2016.058 · doi:10.1109/mite.2016.058
  200. 10.1109/IWCMC.2018.8450537 · DOI

200 of 237 shown

Cited by

See all 840

Metadata

Authors
Qadri, Y. A., Nauman, A., Zikria, Y. B., Vasilakos, A. V., & Kim, S. W.
Venue
IEEE Communications Surveys & Tutorials
Published
2020
Volume
22
Issue
2
Pages
1121-1167
ISSN
  • 1553-877X (ISSN-L)
  • 2373-745X
OpenAlex
W3006191871
Cited by
840
References
22
FWCI
64.94
Type
journal article
Language
en
Open access
closed
Funders
  • National Research Foundation of Korea (2018R1D1A1A09082266, 22A20130012814)
  • Information Technology Research Center (IITP-2019-2016-0-00313)

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

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: The Future of Healthcare Internet of Things: A Survey of Emerging Technologies. https://app.cochat.ai/papers/10.1109/comst.2020.2973314
The paper
Qadri, Y. A., Nauman, A., Zikria, Y. B., Vasilakos, A. V., & Kim, S. W. (2020). The Future of Healthcare Internet of Things: A Survey of Emerging Technologies. IEEE Communications Surveys & Tutorials. https://doi.org/10.1109/comst.2020.2973314

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.