Skip to main content
SpringerLink
Log in

Smart Healthcare, IoT and Machine Learning: A Complete Survey

  • Chapter
  • First Online:
Handbook of Artificial Intelligence in Healthcare

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 212))

Abstract

In the last years monitor the health status of the people has become a one of the major IoT research filed application. Many works and proposal are been presented in literature, some with a specific focus and other with a general purpose objective. From this motivation in this chapter we analyze in dept the state of the art, focusing on the (i) architectural aspects and (ii) algorithm system point of view.

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 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 199.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 199.99
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

References

  1. F. Sadoughi, A. Behmanesh, N. Sayfouri, Internet of things in medicine: a systematic mapping study. J. Biomed. Inf. 103(2020). https://doi.org/10.1016/j.jbi.2020.103383

  2. S. Vidya Priya Darcini, D.P. Isravel, S. Silas (2020) A comprehensive review on the emerging IoT-cloud based technologies for smart healthcare, in 2020 6th International Conference on Advanced Computing and Communication Systems (ICACCS) vol. 9058619 https://doi.org/10.1109/ICACCS48705.2020.9074457

  3. S.S. Gill, P. Garraghan, R. Buyya, Router: fog enabled cloud based intelligent resource management approach for smart home IoT devices. J. Syst. Softw. 154(2019). https://doi.org/10.1016/j.jss.2019.04.058

  4. A. Rajput, T. Brahimi, Chapter 15: Characterizing internet of medical things/personal area networks landscape. Innovat. Health Inf. (2020) https://doi.org/10.1016/B978-0-12-819043-2.00015-0

  5. C. Ana Maria Drăgulinescu, A.F. Manea, O. Fratu, A. Drăgulinescu, LoRa-based medical IoT system architecture and testbed. Wireless Personal Commun. (2020). https://doi.org/10.1007/s11277-020-07235-z

  6. J.L. Shah, H.F. Bhat, CloudIoT for Smart Healthcare: architecture, issues, and challenges. Internet of Things Use Cases for the Healthcare Industry (2020). https://doi.org/10.1007/978-3-030-37526-3_5

  7. R. Jha, V. Bhattacharjee, A. Mustafi, IoT in Healthcare: a big data perspective. Smart Healthcare Anal. IoT Enabled Environ. (2020). https://doi.org/10.1007/978-3-030-37551-5_13

  8. G. Jeya Shree, S. Padmavathi, A fog-based approach for real-time analytics of IoT-enabled healthcare. Internet of Things Use Cases Healthcare Ind (2020). https://doi.org/10.1007/978-3-030-37526-3_11

  9. S.Md. Mahamud, Md.M. Islam, Md.S. Rahman, S.H. Suman, Custody: an IoT based patient surveillance device, in Proceedings of the Future Technologies Conference (FTC) 2018(2019). https://doi.org/10.1007/978-3-030-02686-8_18

  10. U. Syed Tauhid Shah, F. Badshah, F. Dad, N. Amin, M.A. Jan, Cloud-assisted IoT-based smart respiratory monitoring system for asthma patients. Appl. Intell. Technol. Healthcare (2019). https://doi.org/10.1007/978-3-319-96139-2_8

  11. M. Hilal Özcanhan, U. Semih, M.S. Unluturk, Neural network-supported patient-adaptive fall prevention system. Neu. Comput. Appl. (2020). https://doi.org/10.1007/s00521-019-04451-y

  12. O.M. Igwe, Y. Wang, G.C. Giakos, J. Fu, Human activity recognition in smart environments employing margin setting algorithm. J. Amb. Intell. Humanized Comput. (2020). https://doi.org/10.1007/s12652-020-02229-y

  13. X. Zhou, W. Liang, K. I-Kai Wang, H. Wang, L.T. Yang, Q. Jin, Deep learning enhanced human activity recognition for internet of healthcare things. IEEE Int. Things J. 6488907(2020). https://doi.org/10.1109/JIOT.2020.2985082

  14. A. Almazroa, H. Sun, An internet of things (IoT) management system for improving homecare—a case study, in International Symposium on Networks. Computers and Communications (ISNCC) 8894812(2019). https://doi.org/10.1109/ISNCC.2019.8909186

  15. T. Zhang, A. Hassan Sodhro, Z. Luo, N. Zahid, M.W. Nawaz, S. Pirbhulal, M. Muzammal, A joint deep learning and internet of medical things driven framework for elderly patients. IEEE Access 6287639(2020). https://doi.org/10.1109/ACCESS.2020.2989143

  16. Md.A. Sayeed, S.P. Mohanty, E. Kougianos, H.P. Zaveri, Neuro-detect: a machine learning-based fast and accurate seizure detection system in the IoMT. IEEE Trans. Cons. Electron. 30(2019). https://doi.org/10.1109/TCE.2019.2917895

  17. N. Wadhwani, N. Mehta, N. Ruban, IOT based biomedical wireless sensor networks and machine learning algorithms for detection of diseased conditions. 2019 Innovations in Power and Advanced Computing Technologies (i-PACT) vol. 8956176 (2019). https://doi.org/10.1109/i-PACT44901.2019.8960191

  18. A. Athira, T.D. Devika, K.R. Varsha, S. Sanjanaa, S. Bose, Design and development of IOT based multi-parameter patient monitoring system. 2020 6th International Conference on Advanced Computing and Communication Systems (ICACCS) vol. 9058619 (2020). https://doi.org/10.1109/ICACCS48705.2020.9074293

  19. H. Kordestani, R. Mojarad, A. Chibani, A. Osmani, Y. Amirat, K. Barkaoui, W. Zahran, Hapicare: A Healthcare Monitoring System with Self-Adaptive Coaching using Probabilistic Reasoning, in 2019 IEEE/ACS 16th International Conference on Computer Systems and Applications (AICCSA) vol. 9006726 (2019). https://doi.org/10.1109/AICCSA47632.2019.9035291

  20. V. Bianchi, M. Bassoli, G. Lombardo, P. Fornacciari, M. Mordonini, I. De Munari, IoT wearable sensor and deep learning: an integrated approach for personalized human activity recognition in a smart home environment. IEEE Int. Things J. 6488907. (2019). https://doi.org/10.1109/JIOT.2019.2920283

  21. Q. Zhang, D. Zhou, X. Zeng, Hear the heart: Daily cardiac health monitoring using Ear-ECG and machine learning, in IEEE 8th Annual Ubiquitous Computing. Electronics and Mobile Communication Conference (UEMCON) vol. 8234833 (2017). https://doi.org/10.1109/UEMCON.2017.8249110

  22. S. Nookhao, V. Thananant, T. Khunkhao, Development of IoT heartbeat and body temperature monitoring system for community health volunteer. 2020 Joint International Conference on Digital Arts, Media and Technology with ECTI Northern Section Conference on Electrical, Electronics, Computer and Telecommunications Engineering (ECTI DAMT & NCON), vol. 9085868 (2020). https://doi.org/10.1109/ECTIDAMTNCON48261.2020.9090692

  23. A.K.M. Iqtidar Newaz, A. Kumar Sikder, M. Ashiqur Rahman, A. Selcuk Uluagac, HealthGuard: a machine learning-based security framework for smart healthcare systems (2019)

    Google Scholar 

  24. M. Bhatia, S.K. Sood, A comprehensive health assessment framework to facilitate IoT-assisted smart workouts: a predictive healthcare perspective. Comput. Ind. 92–93(2017). https://doi.org/10.1016/j.compind.2017.06.009

  25. H. Qiu, M. Qiu, Z. Lu, Selective encryption on ECG data in body sensor network based on supervised machine learning. Inf. Fusion 55(2020). https://doi.org/10.1016/j.inffus.2019.07.012

  26. Md. Zia Uddin, M. Mehedi Hassan, A. Alsanad, C. Savaglio, A body sensor data fusion and deep recurrent neural network-based behavior recognition approach for robust healthcare. Inf. Fusion 55(2020). https://doi.org/10.1016/j.inffus.2019.08.004

  27. M. Amoon, T. Altameem, A. Altameem, Internet of things sensor assisted security and quality analysis for health care data sets using artificial intelligent based heuristic health management system. Measurement 161(2020). https://doi.org/10.1016/j.measurement.2020.107861

  28. F. Alsubaei, A. Abuhussein, V. Shandilya, S. Shiva, IoMT-SAF: internet of medical things security assessment framework. Internet of Things 8(2019). https://doi.org/10.1016/j.iot.2019.100123

  29. M. Mehedi Hassan, S. Ullah, M.S. Hossain, A. Alelaiwi, An end-to-end deep learning model for human activity recognition from highly sparse body sensor data in Internet Med Things Environ. J Supercomput. (2020). https://doi.org/10.1007/s11227-020-03361-4

  30. A. Kore, S. Patil, IC-MADS: IoT enabled cross layer man-in-middle attack detection system for smart healthcare application. Wireless Personal Commun. (2020). https://doi.org/10.1007/s11277-020-07250-0

  31. P. Gupta, A. Pandey, P. Akshita, A. Sharma, IoT based healthcare kit for diabetic foot ulcer. Proc ICRIC 2019(2020). https://doi.org/10.1007/978-3-030-29407-6_2

  32. S. Ranjani, Rajendran, Machine learning applications for a real-time monitoring of arrhythmia patients using IoT. Internet Things Healthcare Technol. (2021). https://doi.org/10.1007/978-981-15-4112-4_5

  33. B. Mohanta, P. Das, S. Patnaik, Healthcare 5.0: a paradigm shift in digital healthcare system using artificial intelligence. IOT and 5G Commun, in 2019 International Conference on Applied Machine Learning (ICAML), vol. 8967488 (2019). https://doi.org/10.1109/ICAML48257.2019.00044

  34. S.J.A. Aranda, L.P.S. Dias, J.L.V. Barbosa, Carvalho, J.V., J.E. da Rosa Tavares, M.C. Tavares, Collection and analysis of physiological data in smart environments: a systematic mapping. J. Amb Intell. Human. Comput. (2020). https://doi.org/10.1007/s12652-019-01409-9

  35. P. Verma, S. Fatima, Smart healthcare applications and real-time analytics through edge computing. Internet Things Use Cases Healthcare Ind (2020). https://doi.org/10.1007/978-3-030-37526-3_11

  36. L. Greco, G. Percannella, P. Ritrovato, F. Tortorella, M. Vento, Trends in IoT based solutions for health care: moving AI to the edge. Pattern Recogn Lett 135 (2020)

    Google Scholar 

  37. N. Mani, A. Singh, S.L. Nimmagadda, An IoT guided healthcare monitoring system for managing real-time notifications by fog computing services. Proced. Comput. Sci. 167 (2020). https://doi.org/10.1016/j.procs.2020.03.424

  38. I. Machorro-Cano, G. Alor-Hernández, J.O. Olmedo-Aguirre, L. Rodríguez-Mazahua, M.G. Segura-Ozuna, IoT services orchestration and choreography in the healthcare domain. Tech Tools Methodol Appl Glob Supply Chain Ecosyst. (2020). https://doi.org/10.1007/978-3-030-26488-8_19

  39. I. Azimi, J. Takalo-Mattila, A. Anzanpour, A.M. Rahmani, J.-P. Soininen, P. Liljeberg, Empowering healthcare IoT systems with hierarchical edge-based deep learning, 2018 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE), vol. 8641765 (2018). https://doi.org/10.1145/3278576.3278597

  40. A. Darwish, A.E. Hassanien, M. Elhoseny, A.K. Sangaiah, K. Muhammad, The impact of the hybrid platform of internet of things and cloud computing on healthcare systems: opportunities, challenges, and open problems. J. Amb. Intell. Humanized Comput. (2019). https://doi.org/10.1007/s12652-017-0659-1

  41. A. Kobusińska, C. Leung, C.-H. Hsu, S. Raghavendra, V. Chang, Emerging trends, issues and challenges in internet of things, big data and cloud computing. Fut. Generat. Comput. Syst. 87(2018). https://doi.org/10.1016/j.future.2018.05.021

  42. D. Borthakur, H. Dubey, N. Constant, L. Mahler, K. Mankodiya, Smart fog: fog computing framework for unsupervised clustering analytics in wearable internet of things (2017). https://doi.org/10.1109/GlobalSIP.2017.8308687

  43. T.J. Saleem, M.A. Chishti, Deep learning for internet of things data analytics. Proced. Comput. Sci. 163(2019). https://doi.org/10.1016/j.procs.2019.12.120

  44. X. Ma, T. Yao, H. Menglan, Y. Dong, W. Liu, F. Wang, J. Liu, A survey on deep learning empowered IoT applications. IEEE Access 6287639 (2019). https://doi.org/10.1109/ACCESS.2019.2958962

  45. S. Durga, R. Nag, E. Daniel, Survey on machine learning and deep learning algorithms used in internet of things (IoT) healthcare, in 2019 3rd International Conference on Computing Methodologies and Communication (ICCMC), vol. 8811524 (2019). https://doi.org/10.1109/ICCMC.2019.8819806

  46. P. Ghosal, D. Das, I. Das, Extensive survey on cloud-based IoT-healthcare and security using machine learning, in 2018 Fourth International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN), vol. 8716487 (2018). https://doi.org/10.1109/ICRCICN.2018.8718717

  47. S.A. Rokni, H. Ghasemzadeh, Plug-n-learn: automatic learning of computational algorithms in human-centered internet-of-things applications, in 2016 53nd ACM/EDAC/IEEE Design Automation Conference (DAC), vol. 7502236 (2016). https://doi.org/10.1145/2897937.2898066

  48. S. Boudko, H. Abie, Adaptive cybersecurity framework for healthcare internet of things. 2019 13th International Symposium on Medical Information and Communication Technology (ISMICT), vol. 8741513 (2019) https://doi.org/10.1109/ISMICT.2019.8743905

  49. M.L. Challa, K.L.S. Soujanya, C.D. Amulya, Remote monitoring and maintenance of patients via IoT healthcare security and interoperability approach. Cybernet. Cogn. Mach. Lear. Appl. (2020). https://doi.org/10.1007/978-981-15-1632-0_22

  50. G. Rathee, A. Sharma, H. Saini, R. Kumar, R. Iqbal, A hybrid framework for multimedia data processing in IoT-healthcare using blockchain technology. Mult. Tools Appl. (2020). https://doi.org/10.1007/s11042-019-07835-3

    Article  Google Scholar 

  51. H. Hamidi, An approach to develop the smart health using Internet of things and authentication based on biometric technology. Fut. Generation Comput. Syst. 91(2019). https://doi.org/10.1016/j.future.2018.09.024

  52. I. Villanueva-Miranda, H. Nazeran, R. Martinek, A semantic interoperability approach to heterogeneous internet of medical things (IoMT) platforms, in 2018 IEEE 20th International Conference on e-Health Networking, Applications and Services (Healthcom), vol. 8502682 (2018). https://doi.org/10.1109/HealthCom.2018.8531103

  53. X. Cheng, F. Chen, D. Xie, H. Sun, C. Huang, Design of a secure medical data sharing scheme based on blockchain. J. Med. Syst. (2020). https://doi.org/10.1007/s10916-019-1468-1

  54. G. Tripathi, M.A. Ahad, S. Paiva, S2HS- A blockchain based approach for smart healthcare system. Healthcare 8(2020). https://doi.org/10.1016/j.hjdsi.2019.100391

  55. F. Merabet, A. Cherif, M. Belkadi, O. Blazy, Emmanuel conchon, damien sauveron, new efficient M2C and M2M mutual authentication protocols for IoT-based healthcare applications. Peer-to-Peer Network. Appl. (2020). https://doi.org/10.1007/s12083-019-00782-8

  56. W.N. Ismail, M. Mehedi Hassan, H.A. Alsalamah, G. Fortino, CNN-based health model for regular health factors analysis in internet-of-medical things environment. IEEE Access 6287639 (2020). https://doi.org/10.1109/ACCESS.2020.2980938

  57. G. Mylavarapu, J.P. Thomas, A multi-task machine learning approach for comorbid patient prioritization, in 2017 IEEE International Conference on Big Data (Big Data), vol. 8241556 (2017). https://doi.org/10.1109/BigData.2017.8258392

  58. P. Malarvizhi Kumar, U.D. Gandhi, A novel three-tier internet of things architecture with machine learning algorithm for early detection of heart diseases. Comput. Electr. Eng. 65(2018). https://doi.org/10.1016/j.compeleceng.2017.09.001

  59. R.P. França, Y. Iano, B. Ana Carolina Monteiro, R. Arthur, A methodology for improving efficiency in data transmission in healthcare systems. Int. Things for Healthcare Technol. (2021). https://doi.org/10.1007/978-981-15-4112-4_3

  60. N. Moraes, do Nascimento, C. José Pereira de Lucena, FIoT: an agent-based framework for self-adaptive and self-organizing applications based on the Internet of Things. Inf. Sci. 378(2017). https://doi.org/10.1016/j.ins.2016.10.031

  61. Y. Chen, J. Wang, C. Yu, W. Gao, X. Qin, FedHealth: a federated transfer learning framework for wearable healthcare (2019). arxiv.org:1907.09173

  62. S.U. Amin, M. Shamim Hossain, G. Muhammad, M. Alhussein, Md.A. Rahman, Cognitive smart healthcare for pathology detection and monitoring. IEEE Access 6287639(2019). https://doi.org/10.1109/ACCESS.2019.2891390

  63. A. Dridi, S. Sassi, S. Faiz, A smart IoT platform for personalized healthcare monitoring using semantic technologies, in 2017 IEEE 29th International Conference on Tools with Artificial Intelligence (ICTAI), vol. 8344747 (2017). https://doi.org/10.1109/ICTAI.2017.00182

  64. S. Din, A. Paul, Erratum to “Smart health monitoring and management system: Toward autonomous wearable sensing for Internet of Things using big data analytics [Future Gener. Comput. Syst. 91 (2020), 611–619]”. Fut. Generation Computer Systems 108(2019). https://doi.org/10.1016/j.future.2019.06.035

  65. S.A. Khowaja, A.G. Prabono, F. Setiawan, B.N. Yahya, S.-L. Lee, Contextual activity based healthcare internet of things, services, and people (HIoTSP): an architectural framework for healthcare monitoring using wearable sensors. Comput. Netw. 145(2018). https://doi.org/10.1016/j.comnet.2018.09.003

  66. Y. Zhang, J. Cui, K. Ma, H. Chen, J. Zhang, A wristband device for detecting human pulse and motion based on the Internet of Things. Measurement 163(2020). https://doi.org/10.1016/j.measurement.2020.108036

  67. A. Jagtap, A. Chougule, S. Pujari, A. Khamkar, G. Machhale, Intelligent medicine box for medication management using internet-of things. ICDSMLA 2019(2020). https://doi.org/10.1007/978-981-15-1420-3_15

  68. P. Kaur, N. Sharma, A. Singh, B. Gill, CI-DPF: a cloud IoT based framework for diabetes prediction, in IEEE 9th Annual Information Technology. Electronics and Mobile Communication Conference (IEMCON) 8584037 (2018). https://doi.org/10.1109/IEMCON.2018.8614775

  69. A. AbdulGhaffar, S. Mohammad Mostafa, A. Alsaleh, T. Sheltami, E.M. Shakshuki, Internet of things based multiple disease monitoring and health improvement system. J. Amb. Intell. Humanized Comput. (2020). https://doi.org/10.1007/s12652-019-01204-6

  70. V. Karmani, A.A. Chandio, P. Karmani, M. Chandio, I.A. Korejo, Towards self-aware heatstroke early-warning system based on healthcare IoT, in 2019 Third World Conference on Smart Trends in Systems Security and Sustainablity (WorldS4), vol. 8892594 (2019). https://doi.org/10.1109/WorldS4.2019.8904006

  71. N. Nigar, L. Chowdhury, An intelligent children healthcare system by using ensemble technique, Proceedings of International Joint Conference on. Computational Intelligence (2020). https://doi.org/10.1007/978-981-13-7564-4_12

  72. S. Sendra, L. Parra, J. Lloret, J. Tomás, Smart system for children s chronic illness monitoring. Inf. Fusion 40 (2018). https://doi.org/10.1016/j.inffus.2017.06.002

  73. N.G.B. Pulgarín, L.D.C. Aljure, O.J.S. Parra, eHeart-BP, prototype of the internet of things to monitor blood pressure, in 2019 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE), vol. 8905987 (2019). https://doi.org/10.1109/CHASE48038.2019.00025

  74. P. Agarwal, M. Alam, A lightweight deep learning model for human activity recognition on edge devices. Proc. Comput. Sci. 167(2020). https://doi.org/10.1016/j.procs.2020.03.289

  75. U. Khalid, M. Asim, T. Baker, P.C.K. Hung, M.A. Tariq, L. Rafferty, A decentralized lightweight blockchain-based authentication mechanism for IoT systems. Clust. Comput. (2020). https://doi.org/10.1007/s10586-020-03058-6

  76. D. Ravì, C. Wong, B. Lo, G.-Z. Yang, A deep learning approach to on-Node sensor data analytics for mobile or wearable devices. IEEE J. Biomed. Health Inf. 6221020(2017). https://doi.org/10.1109/JBHI.2016.2633287

  77. K.G. Rani Roopha Devi, R. Mahendra Chozhan, R. Murugesan, Cognitive IoT integration for smart healthcare: case study for heart disease detection and monitoring, 2019 International Conference on Recent Advances in Energy-efficient Computing and Communication (ICRAECC), vol. 8975948. (2019) https://doi.org/10.1109/ICRAECC43874.2019.8995049

  78. MMd. Islam, A. Rahaman, Md.R. Islam, Development of smart healthcare monitoring system in IoT environment. SN Comput. Sci. (2020). https://doi.org/10.1007/s42979-020-00195-y

  79. K. Kommuri, V.R. Kolluru, Prototype development of CAQSS health Care system with MQTT protocol by using Atmega328, in 2020 International Conference on Artificial Intelligence and Signal Processing (AISP), vol. 9057353. https://doi.org/10.1109/AISP48273.2020.9073339

  80. H.A. El Zouka, M.M. Hosni, Secure IoT communications for smart healthcare monitoring system. Internet of Things (2019). https://doi.org/10.1016/j.iot.2019.01.003

  81. G. Muhammad, M.F. Alhamid, M. Alsulaiman, B. Gupta, Edge computing with cloud for voice disorder assessment and treatment. IEEE Commun. Magaz. 35(2018). https://doi.org/10.1109/MCOM.2018.1700790

  82. T. Muhammed, R. Mehmood, A. Albeshri, I. Katib, UbeHealth: a personalized ubiquitous cloud and edge-enabled networked healthcare system for smart cities. IEEE Access 6287639 (2018). https://doi.org/10.1109/ACCESS.2018.2846609

  83. M. Hossain, S.M. Riazul Islam, F. Ali, K.-S. Kwak, R. Hasan, An internet of things-based health prescription assistant and its security system design. Fut. Generat. Comput. Syst. 82(2018). https://doi.org/10.1016/j.future.2017.11.020

  84. R.K. Pathinarupothi, P. Durga, E.S. Rangan, IoT-based smart edge for global health: remote monitoring with severity detection and alerts transmission. IEEE Internet of Things J. 6488907 (2019). https://doi.org/10.1109/JIOT.2018.2870068

  85. K.N. Qureshi, S. Din, G. Jeon, F. Piccialli, An accurate and dynamic predictive model for a smart M-Health system using machine learning. Inf. Sci. (2020). https://doi.org/10.1016/j.ins.2020.06.025

  86. D. Mrozek, A. Koczur, B. Małysiak-Mrozek, Fall detection in older adults with mobile IoT devices and machine learning in the cloud and on the edge. Inf. Sci. 537(2020). https://doi.org/10.1016/j.ins.2020.05.070

  87. D.F.S. Santos, H.O. Almeida, A. Perkusich, A personal connected health system for the Internet of Things based on the constrained application protocol. Comput. Electr. Eng. 44(2015). https://doi.org/10.1016/j.compeleceng.2015.02.020

  88. X. Qian, H. Chen, H. Jiang, J. Green, H. Cheng, M.-C. Huang, Wearable computing architecture over distributed deep learning hierarchy: fall detection study. IEEE Sens. J. 7361(2020). https://doi.org/10.1109/JSEN.2020.2988667

  89. Z.Md. Fadlullah, A.-S.K. Pathan, H. Gacanin, On Delay-sensitive healthcare data analytics at the network edge based on deep learning, in 2018 14th International Wireless Communications & Mobile Computing Conference (IWCMC), vol. 8410977 (2018). https://doi.org/10.1109/IWCMC.2018.8450475

  90. W.-J. Chang, L.-B. Chen, C.-H. Hsu, C.-P. Lin, T.-C. Yang, A deep learning-based intelligent medicine recognition system for chronic patients. IEEE Access 6287639 (2019). https://doi.org/10.1109/ACCESS.2019.2908843

  91. J. Azar, A. Makhoul, M. Barhamgi, R. Couturier, An energy efficient IoT data compression approach for edge machine learning. Future Generat. Comput. Syst. 96(2019). https://doi.org/10.1016/j.future.2019.02.005

  92. A. Vishwanatham, N. Ch, S.R. Abhishek, C.R. Ramakrishna, S. Sankara, S. Sanagapati, S. Mohanty, Smart and wearable ECG monitoring system as a point of care (POC) device, in 2018 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS) vol. 8703707 (2018)https://doi.org/10.1109/ANTS.2018.8710115

  93. U. Satija, B. Ramkumar, M.S. Manikandan, Real-time signal quality-aware ECG telemetry system for IoT-based health care monitoring, in IEEE I. Things J. 6488907 (2017). https://doi.org/10.1109/JIOT.2017.2670022

  94. J. Boobalan, M. Malleswaran, A novel and customizable framework for IoT based smart home nursing for elderly care. Emerg. Trends Comput Expert Technol. (2020). https://doi.org/10.1007/978-3-030-32150-5_3

  95. K. Gnana Sheela, A.R. Varghese, Machine Learning based health monitoring system. Mater. Today: Proc. 24(2020). https://doi.org/10.1016/j.matpr.2020.03.603

  96. S.R. Moosavi, T.N. Gia, A.-M. Rahmani, E. Nigussie, H. Tenhunen, SEA: a secure and efficient authentication and authorization architecture for IoT-based healthcare using smart gateways. Proc. Comput. Sci. 52(2015). https://doi.org/10.1016/j.procs.2015.05.013

  97. R. Patan, G.S. Pradeep Ghantasala, R. Sekaran, D. Gupta, M. Ramachandran, Smart healthcare and quality of service in IoT using grey filter convolutional based cyber physical system. Sustain. Cities Soc. 59 (2020). https://doi.org/10.1016/j.scs.2020.102141

  98. Bhatia, M., Kaur, S., S.K. Sood, V. Behal, Internet of things-inspired healthcare system for urine-based diabetes prediction. Artif. Intell. Med. 107(2020). https://doi.org/10.1016/j.artmed.2020.101913

  99. H.B., Hassen, N. Ayari, B. Hamdi, A home hospitalization system based on the internet of things, fog computing and cloud computing. Inf. Med. Unlocked 20(2020). https://doi.org/10.1016/j.imu.2020.100368

  100. S. Tuli, N. Basumatary, S.S. Gill, M. Kahani, R.C. Arya, G.S. Wander, R. Buyya, HealthFog: an ensemble deep learning based smart healthcare system for automatic diagnosis of heart diseases in integrated IoT and fog computing environments. Fut. Gener.Computing Systems 2020(2019). https://doi.org/10.1016/j.future.2019.10.043

  101. J. Yu, B. Fu, A. Cao, Z. He, D. Wu, EdgeCNN: a hybrid architecture for agile learning of healthcare data from IoT devices, in 2018 IEEE 24th International Conference on Parallel and Distributed Systems (ICPADS), vol. 8635632 (2018) . https://doi.org/10.1109/PADSW.2018.8644604

  102. A. Mukherjee, D. De, S.K. Ghosh, FogIoHT: a weighted majority game theory based energy-efficient delay-sensitive fog network for internet of health things. Internet of Things 11 (2020). https://doi.org/10.1016/j.iot.2020.100181

  103. P. Pratim Ray, D. Dash, D. De, Internet of things-based real-time model study on e-healthcare: device, message service and dew computing. Comput. Netw. 149 (2019). https://doi.org/10.1016/j.comnet.2018.12.006

  104. A. Anzanpour, H. Rashid, A.M. Rahmani, A. Jantsch, P. Liljeberg, Energy-efficient and reliable wearable internet-of-things through fog-assisted dynamic goal management. Proc. Comp. Sci. 151(2019). https://doi.org/10.1016/j.procs.2019.04.067

  105. A.M. Rahmani, T.N. Gia, B. Negash, A. Anzanpour, P. Liljeberg, Exploiting smart e-Health gateways at the edge of healthcare internet-of-things: a fog computing approach. Fut. Gener. Comput. Syst. 78(2018). https://doi.org/10.1016/j.future.2017.02.014

  106. G. Neagu, M. Ianculescu, A. Alexandru, V. Florian, C. Zoie Rădulescu, Next generation IoT and its influence on decision-making. An Illustrat. Case Study. Proc. Comput. Sci. 162 (2019). https://doi.org/10.1016/j.procs.2019.12.023

  107. H. Dubey, A. Monteiro, N. Constant, M. Abtahi, D. Borthakur, L. Mahler, Y. Sun, Q. Yang, U. Akbar, K. Mankodiya, Fog computing in medical internet-of-things: architecture. Implement. Appl. (2017). https://doi.org/10.1007/978-3-319-58280-1_11

    Article  Google Scholar 

  108. S. Vaishnavi, T. Sethukarasi, SybilWatch: a novel approach to detect sybil attack in IoT based smart health care. J. Ambient Intell. Humanized Comput. (2020). https://doi.org/10.1007/s12652-020-02189-3

    Article  Google Scholar 

  109. R. Guo, X. Li, D. Zheng, Y. Zhang, An attribute-based encryption scheme with multiple authorities on hierarchical personal health record in cloud. J. Supercomput. (2020). https://doi.org/10.1007/s11227-018-2644-7

    Article  Google Scholar 

  110. Chatterjee, U., D. Sadhukhan, S. Ray, An improved authentication and key agreement protocol for smart healthcare system in the context of internet of things using elliptic curve cryptography, in Proceedings of International Conference on IoT Inclusive Life (ICIIL 2019), NITTTR Chandigarh, India (2020). https://doi.org/10.1007/978-981-15-3020-3_2

  111. J.J. Hathaliya, S. Tanwar, An exhaustive survey on security and privacy issues in Healthcare 4.0. Comput. Commun. 153 (2020). https://doi.org/10.1016/j.comcom.2020.02.018

  112. R.G. Shukla, A. Agarwal, S. Shukla, Chapter 10: blockchain-powered smart healthcare system. Handbook Res. Blockchain Tech. https://doi.org/10.1016/B978-0-12-819816-2.00010-1

  113. H. Rathore, A. Mohamed, M. Guizani, Chapter 8: Blockchain Applications for Healthcare (Energ. Effic. Med. Dev, Healthcare Appl, 2020)

    Google Scholar 

  114. Z. Guan, Z. Lv, D. Xiaojiang, W. Longfei, M. Guizani, Achieving data utility-privacy tradeoff in internet of medical things: a machine learning approach. Fut. Generat. Comput. Syst. 98(2019). https://doi.org/10.1016/j.future.2019.01.058

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

  116. A. Pashazadeh, N.J. Navimipour, Big data handling mechanisms in the healthcare applications: a comprehensive and systematic literature review. J. Biomed. Inf. 82(2018). https://doi.org/10.1016/j.jbi.2018.03.014

  117. B. Trevizan, J. Chamby-Diaz, A.L.C. Bazzan, M. Recamonde-Mendoza, A comparative evaluation of aggregation methods for machine learning over vertically partitioned data. Expert Syst. Appl. 152(2020). https://doi.org/10.1016/j.eswa.2020.113406

  118. C. Perera, C. McCormick, A.K. Bandara, B.A. Price, B. Nuseibeh, Privacy-by-design framework for assessing internet of things applications and platforms, in 6th International Conference on the Internet of Things (IoT 16) (2016). https://doi.org/10.1145/2991561.2991566

Download references

Author information

Authors and Affiliations

  1. Computer Science Department, Università Degli Studi di Milano, Via Celoria 18, Milano, MI, Italy

    Valerio Bellandi, Paolo Ceravolo, Ernesto Damiani & Stefano Siccardi

Authors
  1. Valerio Bellandi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Paolo Ceravolo
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ernesto Damiani
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Stefano Siccardi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Valerio Bellandi .

Editor information

Editors and Affiliations

  1. Institute for Intelligent Systems Research and Innovation, Deakin University, Waurn Ponds, VIC, Australia

    Chee-Peng Lim

  2. College of Information Science and Engineering, Ritsumeikan University, Shiga, Japan

    Yen-Wei Chen

  3. Royal Adelaide Hospital, Adelaide, SA, Australia

    Ashlesha Vaidya

  4. Avanti Institute of Cardiology, Nagpur, India

    Charu Mahorkar

  5. KES International, Shoreham-by-Sea, UK

    Lakhmi C. Jain

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

Bellandi, V., Ceravolo, P., Damiani, E., Siccardi, S. (2022). Smart Healthcare, IoT and Machine Learning: A Complete Survey. In: Lim, CP., Chen, YW., Vaidya, A., Mahorkar, C., Jain, L.C. (eds) Handbook of Artificial Intelligence in Healthcare. Intelligent Systems Reference Library, vol 212. Springer, Cham. https://doi.org/10.1007/978-3-030-83620-7_13

Download citation

Publish with us

Policies and ethics

Search

Navigation