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Importance of Fog Computing in Healthcare 4.0

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Fog Computing for Healthcare 4.0 Environments

Part of the book series: Signals and Communication Technology ((SCT))

Abstract

The wide use of Internet-enabled devices has not left the healthcare sector untouched. The health status of each individual is being monitored irrespective of his/her medical conditions. The advent of such medical devices is beneficial not only for patients but also for physicians, hospitals, and insurance companies. It makes healthcare fast, reliable, and hassle-free. People can keep an eye on their blood pressure, pulse rate, etc., and thus take preventive measures on their own. In hospitals too, the Internet of Things (IoT) is being deployed for various tasks such as monitoring oxygen and blood sugar levels, electrocardiograms (ECGs), etc. IoT in healthcare also reduces the cost of various ailments through fast and rigorous data analysis. Prediction of diseases through machine learning techniques based upon the symptoms has become a promising concept. There may also be a situation where real-time analysis is required. In such a latency-sensitive situation, fog computing plays a vital role. Establishing communication every time with the cloud is not required with the introduction of fog and thus the latency is reduced. Healthcare is a latency-sensitive application area. So, the deployment of fog computing in this area is of vital importance. Proper analytics and research may lead to better care, improved treatment, and enhanced patient satisfaction. The chapter discusses the relevance of fog computing in the area with its issues and challenges. Later, the security issues of fog computing in the area have also been highlighted.

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References

  1. What is Industry 4.0—The Industrial Internet of Things (IIoT)? Retrieved November 05, 2019, from https://www.epicor.com/en-ae/resource-center/articles/what-is-industry-4-0/.

  2. Chiang, M., & Zhang, T. (2016). Fog and IoT: An overview of research opportunities. IEEE Internet of Things Journal, 3(6), 854–864.

    Article  Google Scholar 

  3. Tanwar, S., Parekh, K., & Evans, R. (2019). Blockchain-based electronic healthcare record system for Healthcare 4.0 applications. Journal of Information Security and Applications, 50, 1–14.

    Google Scholar 

  4. Tanwar, S., Bhatia, Q., Patel, P., Kumari, A., Singh, P., & Hong, W. (2019). Machine learning adoption in blockchain-based smart applications: The challenges, and a way forward. IEEE Access, 8, 474–488.

    Article  Google Scholar 

  5. Atlam, H. F., Walters, R. J., & Wills, G. B. (2018). Fog computing and the Internet of Things: A review. Big Data and Cognitive Computing, 2(2), 10.

    Article  Google Scholar 

  6. Kraemer, F. A., Braten, A. E., Tamkittikhun, N., & Palma, D. (2017). Fog computing in healthcare—A review and discussion. IEEE Access, 5, 9206–9222.

    Article  Google Scholar 

  7. IoT Healthcare Market. Retrieved October 15, 2019, from https://www.marketsandmarkets.com/Market-Reports/iot-healthcare-market-160082804.html.

  8. Living healthy. Retrieved October 15, 2019, from https://www.anthem.com/blog/living-healthy/top-4-trends-in-health-care-technology/.

  9. Just the facts: 30 telehealth statistics for doctors to know. Retrieved October 15, 2019, from https://www.ortholive.com/blog/just-the-facts-30-telehealth-statistics-for-doctors-to-know.

  10. Aazam, M., & Huh, E.-N. (2014). Fog computing and smart gateway-based communication for cloud of things. In 2014 International conference on future Internet of Things and cloud. Washington, DC: IEEE.

    Google Scholar 

  11. Ramalho, F., Neto, A., Santos, K., & Agoulmine, N. (2015). Enhancing ehealth smart applications: A fog-enabled approach. In 2015 17th international conference on E-health networking, application & services (HealthCom). Washington, DC: IEEE.

    Google Scholar 

  12. Gia, T. N., Jiang, M., Rahmani, A.-M., Westerlund, T., Liljeberg, P., & Tenhunen, H. (2015). Fog computing in healthcare Internet of Things: A case study on ECG feature extraction. In 2015 IEEE international conference on computer and information technology; ubiquitous computing and communications; dependable, autonomic and secure computing; pervasive intelligence and computing. Washington, DC: IEEE.

    Google Scholar 

  13. Tanwar, S., Tyagi, S., & Kumar, N. (Eds.). (2019). Security and privacy of electronics healthcare records (IET book series on e-health technologies) (pp. 1–450). London: The Institution of Engineering and Technology.

    Google Scholar 

  14. Moosavi, S. R., Gia, T. N., Nigussie, E., Rahmani, A. M., Virtanen, S., Tenhunen, H., et al. (2016). End-to-end security scheme for mobility enabled healthcare Internet of Things. Future Generation Computer Systems, 64, 108–124.

    Article  Google Scholar 

  15. Khan, S., Parkinson, S., & Qin, Y. (2017). Fog computing security: A review of current applications and security solutions. Journal of Cloud Computing, 6(1), 19.

    Article  Google Scholar 

  16. Barik, R. K., Dubey, H., & Mankodiya, K. (2017). SOA-FOG: Secure service-oriented edge computing architecture for smart health big data analytics. In 2017 IEEE global conference on signal and information processing (GlobalSIP). Washington, DC: IEEE.

    Google Scholar 

  17. Al Hamid, H. A., Rahman, S. M. M., Hossain, M. S., Almogren, A., & Alamri, A. (2017). A security model for preserving the privacy of medical big data in a healthcare cloud using a fog computing facility with pairing-based cryptography. IEEE Access, 5, 22313–22328.

    Article  Google Scholar 

  18. Manogaran, G., Varatharajan, R., Lopez, D., Kumar, P. M., Sundarasekar, R., & Thota, C. (2017). A new architecture of Internet of Things and big data ecosystem for secured smart healthcare monitoring and alerting system. Future Generation Computer Systems, 82, 375–387.

    Article  Google Scholar 

  19. Vora, J., Tanwar, S., Tyagi, S., Kumar, N., & Rodrigues, J. J. P. C. (2017). FAAL: Fog computing-based patient monitoring system for ambient assisted living. In 2017 IEEE 19th international conference on e-health networking, applications and services (Healthcom). Washington, DC: IEEE.

    Google Scholar 

  20. Gia, T. N., Jiang, M., Sarker, V. K., Rahmani, A. M., Westerlund, T., Liljeberg, P., et al. (2017). Low-cost fog-assisted health-care IoT system with energy-efficient sensor nodes. In 2017 13th international wireless communications and mobile computing conference (IWCMC). Washington, DC: IEEE.

    Google Scholar 

  21. Fernandez, F., & Pallis, G. C. (2014). Opportunities and challenges of the Internet of Things for healthcare: Systems engineering perspective. In 2014 Fourth international conference on wireless mobile communication and healthcare-transforming healthcare through innovations in mobile and wireless technologies (MOBIHEALTH). Washington, DC: IEEE.

    Google Scholar 

  22. Kanth, R. K., Liljeberg, P., Westerlund, T., Kumar, H., Tenhunen, H., Wan, Q., et al. (2014). Information and communication system technology’s impacts on personalized and pervasive healthcare: A technological survey. In 2014 IEEE conference on Norbert Wiener in the 21st century (21CW). Washington, DC: IEEE.

    Google Scholar 

  23. Cao, Y., Chen, S., Hou, P., & Brown, D. (2015). FAST: A fog computing assisted distributed analytics system to monitor fall for stroke mitigation. In 2015 IEEE international conference on networking, architecture and storage (NAS). Washington, DC: IEEE.

    Google Scholar 

  24. Fratu, O., Pena, C., Craciunescu, R., & Halunga, S. (2015). Fog computing system for monitoring Mild Dementia and COPD patients—Romanian case study. In 2015 12th international conference on telecommunication in modern satellite, cable and broadcasting services (TELSIKS). Washington, DC: IEEE.

    Google Scholar 

  25. Gu, L., Zeng, D., Guo, S., Barnawi, A., & Xiang, Y. (2015). Cost efficient resource management in fog computing supported medical cyber-physical system. IEEE Transactions on Emerging Topics in Computing, 5(1), 108–119.

    Article  Google Scholar 

  26. Prieto González, L., Jaedicke, C., Schubert, J., & Stantchev, V. (2016). Fog computing architectures for healthcare: Wireless performance and semantic opportunities. Journal of Information, Communication and Ethics in Society, 14(4), 334–349.

    Article  Google Scholar 

  27. Masip-Bruin, X., Marín-Tordera, E., Alonso, A., & Garcia, J. (2016). Fog-to-cloud computing (F2C): The key technology enabler for dependable e-health services deployment. In 2016 Mediterranean ad hoc networking workshop (Med-Hoc-Net). Washington, DC: IEEE.

    Google Scholar 

  28. Chakraborty, S., Bhowmick, S., Talaga, P., & Agrawal, D. P. (2016). Fog networks in healthcare application. In 2016 IEEE 13th international conference on mobile ad hoc and sensor systems (MASS). Washington, DC: IEEE.

    Google Scholar 

  29. Azimi, I., Anzanpour, A., Rahmani, A. M., Liljeberg, P., & Salakoski, T. (2016). Medical warning system based on Internet of Things using fog computing. In 2016 international workshop on big data and information security (IWBIS). Washington, DC: IEEE.

    Google Scholar 

  30. Monteiro, A., Dubey, H., Mahler, L., Yang, Q., & Mankodiya, K. (2016). Fit: A fog computing device for speech tele-treatments. In 2016 IEEE international conference on smart computing (SMARTCOMP). Washington, DC: IEEE.

    Google Scholar 

  31. Elmisery, A. M., Rho, S., & Botvich, D. (2016). A fog-based middleware for automated compliance with OECD privacy principles in internet of healthcare things. IEEE Access, 4, 8418–8441.

    Article  Google Scholar 

  32. Ahmad, M., Amin, M. B., Hussain, S., Kang, B. H., Cheong, T., & Lee, S. (2016). Health fog: A novel framework for health and wellness applications. The Journal of Supercomputing, 72(10), 3677–3695.

    Article  Google Scholar 

  33. Sood, S. K., & Mahajan, I. (2017). A fog-based healthcare framework for chikungunya. IEEE Internet of Things Journal, 5(2), 794–801.

    Article  Google Scholar 

  34. Mahmoud, M. M. E., Rodrigues, J. J. P. C., Saleem, K., Al-Muhtadi, J., Kumar, N., & Korotaev, V. (2018). Towards energy-aware fog-enabled cloud of things for healthcare. Computers & Electrical Engineering, 67, 58–69.

    Article  Google Scholar 

  35. Rahmani, A. M., Gia, T. N., Negash, B., Anzanpour, A., Azimi, I., Jiang, M., et al. (2018). Exploiting smart e-Health gateways at the edge of healthcare Internet-of-Things: A fog computing approach. Future Generation Computer Systems, 78, 641–658.

    Article  Google Scholar 

  36. Farahani, B., Firouzi, F., Chang, V., Badaroglu, M., Constant, N., & Mankodiya, K. (2018). Towards fog-driven IoT eHealth: Promises and challenges of IoT in medicine and healthcare. Future Generation Computer Systems, 78, 659–676.

    Article  Google Scholar 

  37. Kumari, A., Tanwar, S., Tyagi, S., & Kumar, N. (2018). Fog computing for Healthcare 4.0 environment: Opportunities and challenges. Computers & Electrical Engineering, 72, 1–13.

    Article  Google Scholar 

  38. Wu, W., Pirbhulal, S., Sangaiah, A. K., Mukhopadhyay, S. C., & Li, G. (2018). Optimization of signal quality over comfortability of textile electrodes for ECG monitoring in fog computing based medical applications. Future Generation Computer Systems, 86, 515–526.

    Article  Google Scholar 

  39. Vijayakumar, V., Malathi, D., Subramaniyaswamy, V., Saravanan, P., & Logesh, R. (2018). Fog computing-based intelligent healthcare system for the detection and prevention of mosquito-borne diseases. Computers in Human Behavior, 100, 275–285.

    Article  Google Scholar 

  40. Abdel-Basset, M., & Mohamed, M. (2019). A novel and powerful framework based on neutrosophic sets to aid patients with cancer. Future Generation Computer Systems, 98, 144–153.

    Article  Google Scholar 

  41. Nikoloudakis, Y., Pallis, E., Mastorakis, G., Mavromoustakis, C. X., Skianis, C., & Markakis, E. K. (2019). Vulnerability assessment as a service for fog-centric ICT ecosystems: A healthcare use case. Peer-to-Peer Networking and Applications, 1216, 1224–1229.

    Google Scholar 

  42. Islam, N., Faheem, Y., Din, I. U., Talha, M., Guizani, M., & Khalil, M. (2019). A blockchain-based fog computing framework for activity recognition as an application to e-Healthcare services. Future Generation Computer Systems, 100, 569–578.

    Article  Google Scholar 

  43. Tang, W., Zhang, K., Zhang, D., Ren, J., Zhang, Y., & Shen, X. S. (2019). Fog-enabled smart health: Toward cooperative and secure healthcare service provision. IEEE Communications Magazine, 57(5), 42–48.

    Article  Google Scholar 

  44. Pravin, A., Prem Jacob, T., & Nagarajan, G. (2019). An intelligent and secure healthcare framework for the prediction and prevention of Dengue virus outbreak using fog computing. Health and Technology, 10, 303–311.

    Article  Google Scholar 

  45. Queralta, J., Pena, T. N. G., Tenhunen, H., & Westerlund, T. (2019). Edge-AI in LoRa-based health monitoring: Fall detection system with fog computing and LSTM recurrent neural networks. In 2019 42nd international conference on telecommunications and signal processing (TSP). Washington, DC: IEEE.

    Google Scholar 

  46. Tuli, S., Basumatary, N., Gill, S. S., Kahani, M., Arya, R. C., Wander, G. S., et al. (2019). HealthFog: An ensemble deep learning based Smart Healthcare System for Automatic Diagnosis Of Heart Diseases in integrated IoT and fog computing environments. Future Generation Computer Systems, 104, 187–200.

    Article  Google Scholar 

  47. Gu, J., Huang, R., Jiang, L., Qiao, G., Du, X., & Guizani, M. (2019). A fog computing solution for context-based privacy leakage detection for android healthcare devices. Sensors, 19(5), 1184.

    Article  Google Scholar 

  48. Findings from the Global Burden of Disease Study 2017. Retrieved October 19, 2019, from http://www.healthdata.org/sites/default/files/files/policy_report/2019/GBD_2017_Booklet.pdf.

  49. A research report on IoT Healthcare Market. Retrieved October 10, 2019, from https://www.marketsandmarkets.com/PressReleases/iot-healthcare.asp.

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Kaur, J., Verma, R., Alharbe, N.R., Agrawal, A., Khan, R.A. (2021). Importance of Fog Computing in Healthcare 4.0. In: Tanwar, S. (eds) Fog Computing for Healthcare 4.0 Environments. Signals and Communication Technology. Springer, Cham. https://doi.org/10.1007/978-3-030-46197-3_4

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  • DOI: https://doi.org/10.1007/978-3-030-46197-3_4

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