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Healthcare Application System with Cyber-Security Using Machine Learning Techniques

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Expert Clouds and Applications

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 444))

Abstract

Compared to last year Internet of Things Intelligent (IoT), this year’s IoT brings a significant increase in intelligence, or “things,” into the Internet of Things (IoT). Regarding the significance of subjective pain inside such an active communication network, we are not yet beyond the reach of artificial intelligence, but we are close. Pain, as well as organs of emotions and ideas (cell phones and tablets), appear alongside home appliances and mobile devices (such as smartphones and tablets). In addition, several of these devices are accessible in markets all over the globe. When it comes to current Internet problems, the source of the pain is the access to Internet Connectivity that they provide. In order to reap the advantages of research capacity solutions, artificial intelligence methods use intelligence. Globally, health-care services are among the most significant uses that the Internet of Things (IoT) has made possible. In order for patients to monitor their health in real time, advanced sensors may be worn on their bodies or implanted into their organs. Afterwards, the information may be analysed, grouped, and prioritised if necessary. When physicians work with algorithms, they may make adjustments to their treatment plans while simultaneously ensuring that patients get cost-effective health care.

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References

  1. H.T. Sullivan, S. Sahasrabudhe, Envisioning inclusive futures: technology-based assistive sensory and action substitution. Futur. J. 87, 140–148 (2017)

    Article  Google Scholar 

  2. Y. Yin, Y. Zeng, X. Chen, Y. Fan, The Internet of Things in healthcare: an overview. J. Ind. Inf. Integr. 1, 3–13 (2016)

    Google Scholar 

  3. H.N. Saha, S. Auddy, S. Pal, Health monitoring using Internet of Things (IoT). IEEE J. 69–73 (2017)

    Google Scholar 

  4. S.F. Khan, Health care monitoring system in Internet of Things (loT) by using RFID, in IEEE International Conference on Industrial Technology and Management (2017), pp. 198–204

    Google Scholar 

  5. M. Hassanalieragh, A. Page, T. Soyata, G. Sharma, Health monitoring and management using Internet-of-Things (IoT) sensing with cloud-based processing: opportunities and challenges (2015)

    Google Scholar 

  6. M.S.D. Gupta, V. Patchava, V. Menezes, Healthcare based on iot using raspberry pi, in 2015 International Conference on Green Computing and Internet of Things (ICGCIoT), Oct 2015, pp. 796–799

    Google Scholar 

  7. P. Gupta, D. Agrawal, J. Chhabra, P.K. Dhir, Iot based smart healthcare kit, in 2016 International Conference on Computational Techniques in Information and Communication Technologies (ICCTICT), Mar 2016, pp. 237–242

    Google Scholar 

  8. N.V. Lopes, F. Pinto, P. Furtado, J. Silva, Iot architecture proposal for disabled people, in 2014 IEEE 10th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), Oct 2014, pp. 152–158

    Google Scholar 

  9. R. Nagavelli, C.V. Guru Rao, Degree of disease possibility (ddp): a mining based statistical measuring approach for disease prediction in health care data mining, in International Conference on Recent Advances and Innovations in Engineering (ICRAIE-2014), May 2014, pp. 1–6

    Google Scholar 

  10. P.K. Sahoo, S.K. Mohapatra, S.L. Wu, Analyzing healthcare big data with prediction for future health condition. IEEE Access 4, 9786–9799 (2016). ISSN 2169-3536

    Google Scholar 

  11. B. Krishnan, S.S. Sai, S.B. Mohanthy, Real time internet application with distributed flow environment for medical IoT, in International Conference on Green Computing and Internet of Things, Noida (2015), pp. 832–837

    Google Scholar 

  12. V. Arulkumar, C. Puspha Latha, D. Jr Dasig, Concept of implementing big data in smart city: applications, services, data security in accordance with Internet of Things and AI. Int. J. Recent Technol. Eng. 8(3) (2019)

    Google Scholar 

  13. D. Azariadi, V. Tsoutsouras, S. Xydis, D. Soudris, ECG signal analysis and arrhythmia detection on IoT wearable medical devices, in 5th International Conference on Modern Circuits and Systems Technologies, Thessaloniki (2016), pp. 1–4

    Google Scholar 

  14. A. Mohan, Cyber security for personal medical devices Internet of Things, in IEEE International Conference on Distributed Computing in Sensor Systems, Marina Del Rey, CA (2014), pp. 372–374

    Google Scholar 

  15. L.Y. Yeh, P.Y. Chiang, Y.L. Tsai, J.L. Huang, Cloudbased fine-grained health information access control framework for lightweight IoT devices with dynamic auditing and attribute revocation. IEEE Trans. Cloud Comput. 99, 1–13 (2015). IoT-based health monitoring system for active and assisted living 19

    Google Scholar 

  16. V. Arulkumar, An intelligent technique for uniquely recognising face and finger image using learning vector quantisation (LVQ)-based template key generation. Int. J. Biomed. Eng. Technol. 26(3/4), 237–49 (2018)

    Google Scholar 

  17. P. Porambage, A. Braeken, A. Gurtov, M. Ylianttila, S. Spinsante, Secure end-to-end communication for constrained devices in IoT-enabled ambient assisted living systems, in IEEE 2nd World Forum on Internet of Things, Milan (2015), pp. 711–714

    Google Scholar 

  18. K. Yelamarthi, B.P. DeJong, K. Laubhan, A kinect-based vibrotactile feedback system to assist the visually impaired (2017)

    Google Scholar 

  19. X.-W. Chen, X. Lin, Big data deep learning: challenges and perspectives. IEEE access 2, 514–525 (2014)

    Article  Google Scholar 

  20. M. Siekkinen, M. Hiienkari, J. Nurminen, J. Nieminen, How low energy is bluetooth low energy? Comparative measurements with zigbee/802.15.4, in Wireless Communications and Networking Conference Workshops (WCNCW) (IEEE, 2012), Apr 2012, pp. 232–237

    Google Scholar 

  21. N. Bui, M. Zorzi, Health care applications: a solution based on the internet of things, in Proceedings of the 4th Int. Symposium on Applied Sciences in Biomedical and Communication Technologies, ser. ISABEL’11 (ACM, New York, 2011), pp. 131:1–131:5

    Google Scholar 

  22. K. Laubhan, M. Trent, B. Root, A. Abdelgawad, K. Yelamarthi, A wearable portable electronic travel aid for the blind, in IEEE International Conference on Electrical, Electronics, and Optimization Techniques (2016)

    Google Scholar 

  23. M. Li, S. Yu, Y. Zheng, K. Ren, W. Lou, Scalable and secure sharing of personal health records in cloud computing using attribute based encryption. IEEE Trans. Parallel Distrib. Syst. 24(1), 131–143 (2013). C. Bishop, Pattern Recognition and Machine Learning. Springer, New York (2006)

    Google Scholar 

  24. V. Arulkumar, C. Selvan, V. Vimal Kumar, Big data analytics in healthcare industry. An analysis of healthcare applications in machine learning with big data analytics. IGI Global Big Data Analyt. Sustain. Comput. 8(3) (2019)

    Google Scholar 

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Correspondence to C. Selvan .

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Selvan, C., Jenifer Grace Giftlin, C., Aruna, M., Sridhar, S. (2022). Healthcare Application System with Cyber-Security Using Machine Learning Techniques. In: Jacob, I.J., Kolandapalayam Shanmugam, S., Bestak, R. (eds) Expert Clouds and Applications. Lecture Notes in Networks and Systems, vol 444. Springer, Singapore. https://doi.org/10.1007/978-981-19-2500-9_9

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