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Adoption of Fog Computing in Healthcare 4.0

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Fog Computing for Healthcare 4.0 Environments

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Abstract

Health issues (concerning human being) are critical nowadays. Due to heavy workload and less time, human beings do not have sufficient time to consult a doctor regarding their health. Healthcare industry has a different generation like healthcare 1.0 to healthcare 4.0. Healthcare 3.0 is focused on hospitals, where patients have to visit multiple hospitals for their routine examination, making them suffer through long-lasting sickness. It turns a patient into a lengthy process of examination and also it increases the overall budget of treatment. However, with the help of Fog Computing (FC), the above-said problem can be minimized by investing less money on computing and storage facility in respect of data related to patients. Healthcare 4.0 is working on FC platform. FC extends cloud computing platforms with additional computing, storage and networking resources, placed near end-user devices. FC deploying fog nodes throughout the network is deployed in target areas like cars and offices etc. When an IoT device generates the data, then it will be analyzed by one of the fog nodes without sending back to the cloud. The main aim of this chapter is to provide a systematic view of the technology used for FC in healthcare 4.0. This chapter also gives a comparative study of the different version of healthcare with current version 4.0. Further, different researchers view about healthcare industry is discussed in detail. This chapter also discussed the importance of FC in healthcare with the help of some case studies for better understanding in solving health-related issues.

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References

  1. Padfield, J. R. (2013). A study of innovation processes used in the United States healthcare system. Doctoral dissertation, Purdue University.

    Google Scholar 

  2. Sun, J., Gao, M., Wang, Q., Jiang, M., Zhang, X., & Schmitt, R. (2018). Smart services for enhancing personal competence in industrie 4.0 digital factory. LogForum, 14(1), 51–57.

    Article  Google Scholar 

  3. Truong, H. L., & Dustdar, S. (2015). Principles for engineering IoT cloud systems. IEEE Cloud Computing, 2(2), 68–76.

    Article  Google Scholar 

  4. Shankar, K., Lakshmanaprabu, S. K., Khanna, A., Tanwar, S., Rodrigues, J. J., & Roy, N. R. (2019). Alzheimer detection using Group Grey Wolf Optimization based features with convolutional classifier. Computers & Electrical Engineering, 77, 230–243.

    Article  Google Scholar 

  5. Kumari, A., Tanwar, S., Tyagi, S., Kumar, N., Maasberg, M., & Choo, K. K. R. (2018). Multimedia big data computing and Internet of Things applications: A taxonomy and process model. Journal of Network and Computer Applications, 124, 169–195.

    Article  Google Scholar 

  6. Weisgrau, S. (1995). Issues in rural health: Access, hospitals, and reform. Health Care Financing Review, 17(1), 1.

    Google Scholar 

  7. Kaneriya, S., Tanwar, S., Buddhadev, S., Verma, J. P., Tyagi, S., Kumar, N., et al. (2018, May). A range-based approach for long-term forecast of weather using probabilistic markov model. In 2018 IEEE international conference on communications workshops (ICC workshops) (pp. 1–6). Washington, DC: IEEE.

    Google Scholar 

  8. Kaneriya, S., Vora, J., Tanwar, S., & Tyagi, S. (2019, May). Standardising the use of duplex channels in 5G-WiFi networking for ambient assisted living. In 2019 IEEE international conference on communications workshops (ICC workshops) (pp. 1–6). Washington, DC: IEEE.

    Google Scholar 

  9. Mittal, M., Tanwar, S., Agarwal, B., & Goyal, L. M. (2019). Energy conservation for IoT devices concepts, paradigms and solutions. In Studies in systems, decision and control (pp. 1–356). Singapore: Springer Nature Singapore Pte Ltd..

    Google Scholar 

  10. Bodkhe, U., Bhattacharya, P., Tanwar, S., Tyagi, S., Kumar, N., & Obaidat, M. S. (2019, August). BloHosT: Blockchain enabled smart tourism and hospitality management. In 2019 international conference on computer, information and telecommunication systems (CITS) (pp. 1–5). Washington, DC: IEEE.

    Google Scholar 

  11. Gupta, R., Tanwar, S., Tyagi, S., Kumar, N., Obaidat, M. S., & Sadoun, B. (2019, August). HaBiTs: Blockchain-based telesurgery framework for healthcare 4.0. In 2019 international conference on computer, information and telecommunication systems (CITS) (pp. 1–5). Washington, DC: IEEE.

    Google Scholar 

  12. Kabra, N., Bhattacharya, P., Tanwar, S., & Tyagi, S. (2020). MudraChain: Blockchain-based framework for automated cheque clearance in financial institutions. Future Generation Computer Systems, 102, 574–587.

    Article  Google Scholar 

  13. Mistry, I., Tanwar, S., Tyagi, S., & Kumar, N. (2020). Blockchain for 5G-enabled IoT for industrial automation: A systematic review, solutions, and challenges. Mechanical Systems and Signal Processing, 135, 106382.

    Article  Google Scholar 

  14. Pramanik, P. K. D., Pareek, G., & Nayyar, A. (2019). Security and privacy in remote healthcare: Issues, solutions, and standards. In Telemedicine technologies (pp. 201–225). Cambridge, MA: Academic Press.

    Chapter  Google Scholar 

  15. Gupta, M., & Singla, N. (2019). Evolution of cloud in big data with hadoop on docker platform. In Web services: Concepts, methodologies, tools, and applications (pp. 1601–1622). Hershey, PA: IGI Global.

    Google Scholar 

  16. Srivastava, A., Singh, S. K., Tanwar, S., & Tyagi, S. (2017, September). Suitability of big data analytics in Indian banking sector to increase revenue and profitability. In 2017 3rd international conference on advances in computing, communication & automation (ICACCA) (Fall) (pp. 1–6). Washington, DC: IEEE.

    Google Scholar 

  17. Tanwar, S., Tyagi, S., & Kumar, N. (Eds.). (2019). Multimedia big data computing for IoT applications: Concepts, paradigms and solutions (Vol. 163, pp. 1–425). Singapore: Springer Nature Singapore Pte Ltd..

    Google Scholar 

  18. Ahmed, A., Arkian, H., Battulga, D., Fahs, A.J., Farhadi, M., Giouroukis, D., et al. (2019). Fog computing applications: Taxonomy and requirements. arXiv preprint: arXiv:1907.11621.

    Google Scholar 

  19. Kumari, A., Tanwar, S., Tyagi, S., Kumar, N., Parizi, R. M., & Choo, K. K. R. (2019). Fog data analytics: A taxonomy and process model. Journal of Network and Computer Applications, 128, 90–104.

    Article  Google Scholar 

  20. Alfian, G., Syafrudin, M., Ijaz, M., Syaekhoni, M., Fitriyani, N., & Rhee, J. (2018). A personalized healthcare monitoring system for diabetic patients by utilizing BLE-based sensors and real-time data processing. Sensors, 18(7), 2183.

    Article  Google Scholar 

  21. Dang, L. M., Piran, M., Han, D., Min, K., & Moon, H. (2019). A survey on internet of things and cloud computing for healthcare. Electronics, 8(7), 768.

    Article  Google Scholar 

  22. Bonomi, F., Milito, R., Zhu, J., & Addepalli, S. (2012, August). Fog computing and its role in the internet of things. In Proceedings of the first edition of the MCC workshop on mobile cloud computing (pp. 13–16). New York: ACM.

    Chapter  Google Scholar 

  23. George, A., Dhanasekaran, H., Chittiappa, J. P., Challagundla, L. A., Nikkam, S. S., & Abuzaghleh, O. (2018, May). Internet of Things in health care using fog computing. In 2018 IEEE Long Island Systems, Applications and Technology conference (LISAT) (pp. 1–6). Washington, DC: IEEE.

    Google Scholar 

  24. 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 

  25. Kumari, A., Tanwar, S., Tyagi, S., & Kumar, N. (2018). Verification and validation techniques for streaming big data analytics in internet of things environment. IET Networks, 8(2), 92–100.

    Google Scholar 

  26. Elhoseny, M., Abdelaziz, A., Salama, A. S., Riad, A. M., Muhammad, K., & Sangaiah, A. K. (2018). A hybrid model of internet of things and cloud computing to manage big data in health services applications. Future Generation Computer Systems, 86, 1383–1394.

    Article  Google Scholar 

  27. Sheth, S. (2019, December). Diabetes management: Glucose monitors that connect to your smart phone. Retrieved from: https://dlife.com/diabetes-management-glucose-monitors-that-connect-to-your-smart-phone/.

  28. 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 

  29. Tanwar, S., Ramani, T., & Tyagi, S. (2017, August). Dimensionality reduction using PCA and SVD in big data: A comparative case study. In International conference on future internet technologies and trends (pp. 116–125). Cham: Springer.

    Google Scholar 

  30. Vora, J., Kaneriya, S., Tanwar, S., Tyagi, S., Kumar, N., & Rodrigues, J. J. (2019, December). HRIDaaY: Ballistocardiogram-based heart rate monitoring using fog computing. In 2019 IEEE global communications conference (GLOBECOM-2019) (pp. 1–6). Washington, DC: IEEE.

    Google Scholar 

  31. Gor, M., Vora, J., Tanwar, S., Tyagi, S., Kumar, N., Obaidat, M. S., et al. (2017, July). GATA: GPS-Arduino based Tracking and Alarm system for protection of wildlife animals. In 2017 international conference on computer, information and telecommunication systems (CITS) (pp. 166–170). Washington, DC: IEEE.

    Chapter  Google Scholar 

  32. Gia, T. N., Dhaou, I. B., Ali, M., Rahmani, A. M., Westerlund, T., Liljeberg, P., et al. (2019). Energy efficient fog-assisted IoT system for monitoring diabetic patients with cardiovascular disease. Future Generation Computer Systems, 93, 198–211.

    Article  Google Scholar 

  33. Guan, Y., Shao, J., Wei, G., & Xie, M. (2018). Data security and privacy in fog computing. IEEE Network, 32(5), 106–111.

    Article  Google Scholar 

  34. Tanwar, S., Vora, J., Kaneriya, S., & Tyagi, S. (2017, September). Fog-based enhanced safety management system for miners. In 2017 3rd international conference on advances in computing, communication & automation (ICACCA) (Fall) (pp. 1–6). Washington, DC: IEEE.

    Google Scholar 

  35. Al Faruque, M. A., & Vatanparvar, K. (2015). Energy management-as-a-service over fog computing platform. IEEE Internet of Things Journal, 3(2), 161–169.

    Article  Google Scholar 

  36. Elrod, J. K., & Fortenberry, J. L. (2017). Peering beyond the walls of healthcare institutions: A catalyst for innovation. BMC Health Services Research, 17(1), 402.

    Article  Google Scholar 

  37. Vora, J., Nayyar, A., Tanwar, S., Tyagi, S., Kumar, N., Obaidat, M. S., et al. (2018, December). BHEEM: A Blockchain-based framework for securing electronic health records. In 2018 IEEE Globecom workshops (GC Wkshps) (pp. 1–6). Washington, DC: IEEE.

    Google Scholar 

  38. Beggelman, M. (2008). Virtual reasoning redefining healthcare through health 3.0. White Paper.

    Google Scholar 

  39. Abidi, B., Jilbab, A., & Haziti, M. E. (2017). Wireless sensor networks in biomedical: Wireless body area networks. In Europe and MENA cooperation advances in information and communication technologies (pp. 321–329). Cham: Springer.

    Chapter  Google Scholar 

  40. Tanwar, S., Parekh, K., & Evans, R. (2020). Blockchain-based electronic healthcare record system for healthcare 4.0 applications. Journal of Information Security and Applications, 50, 102407.

    Article  Google Scholar 

  41. Vora, J., Tanwar, S., Tyagi, S., Kumar, N., & Rodrigues, J. J. (2017, October). Home-based exercise system for patients using IoT enabled smart speaker. In 2017 IEEE 19th international conference on e-health networking, applications and services (Healthcom) (pp. 1–6). Washington, DC: IEEE.

    Google Scholar 

  42. Hathaliya, J. J., Tanwar, S., Tyagi, S., & Kumar, N. (2019). Securing electronics healthcare records in Healthcare 4.0: A biometric-based approach. Computers & Electrical Engineering, 76, 398–410.

    Article  Google Scholar 

  43. Tanwar, S., Thakkar, K., Thakor, R., & Singh, P. K. (2018). M-Tesla-based security assessment in wireless sensor network. Procedia Computer Science, 132, 1154–1162.

    Article  Google Scholar 

  44. Wehde, M. (2019). Healthcare 4.0. IEEE Engineering Management Review, 47(3), 24–28.

    Article  Google Scholar 

  45. Gupta, M., & Dahiya, D. (2016). Performance evaluation of classification algorithms on different datasets. Indian Journal of Science and Technology and Technology, 9(40), 1–6. https://doi.org/10.17485/ijst/2016/v9i40/99425.

    Article  Google Scholar 

  46. Peralta, G., Iglesias-Urkia, M., Barcelo, M., Gomez, R., Moran, A., & Bilbao, J. (2017, May). Fog computing based efficient IoT scheme for the Industry 4.0. In 2017 IEEE international workshop of electronics, control, measurement, signals and their application to mechatronics (ECMSM) (pp. 1–6). Washington, DC: IEEE.

    Google Scholar 

  47. Vora, J., Kaneriya, S., Tanwar, S., & Tyagi, S. (2018, February). Performance evaluation of SDN based virtualization for data center networks. In 2018 3rd international conference on internet of things: Smart innovation and usages (IoT-SIU) (pp. 1–5). Washington, DC: IEEE.

    Google Scholar 

  48. Vora, J., Italiya, P., Tanwar, S., Tyagi, S., Kumar, N., Obaidat, M. S., et al. (2018, July). Ensuring privacy and security in e-health records. In 2018 international conference on computer, information and telecommunication systems (CITS) (pp. 1–5). Washington, DC: IEEE.

    Google Scholar 

  49. Raghupathi, W., & Raghupathi, V. (2014). Big data analytics in healthcare: Promise and potential. Health Information Science and Systems, 2(1), 3.

    Article  Google Scholar 

  50. Prasad, V. K., Bhavsar, M. D., & Tanwar, S. (2019). Influence of monitoring: Fog and edge computing. Scalable Computing: Practice and Experience, 20(2), 365–376.

    Google Scholar 

  51. Singh, S. P., Nayyar, A., Kaur, H., & Singla, A. (2019). Dynamic task scheduling using balanced VM allocation policy for fog computing platforms. Scalable Computing: Practice and Experience, 20(2), 433–456.

    Google Scholar 

  52. Zhou, Y., Shi, W., & Song, F. (2018). A smart collaborative policy for mobile fog computing in rural vitalization. Wireless Communications and Mobile Computing, 2018, 1–10.

    Google Scholar 

  53. Vora, J., Kaneriya, S., Tanwar, S., Tyagi, S., Kumar, N., & Obaidat, M. S. (2019). TILAA: Tactile internet-based ambient assistant living in fog environment. Future Generation Computer Systems, 98, 635–649.

    Article  Google Scholar 

  54. Gupta, M., Solanki, V. K., & Singh, V. K. (2017). A novel framework to use association rule mining for classification of traffic accident severity. Ingeniería Solidaria, 13(21), 37–44.

    Article  Google Scholar 

  55. Gupta, M., Solanki, V. K., Singh, V. K., & García-Díaz, V. (2018). Data mining approach of accident occurrences identification with effective methodology and implementation. International Journal of Electrical and Computer Engineering, 8(5), 4033.

    Google Scholar 

  56. Vora, J., DevMurari, P., Tanwar, S., Tyagi, S., Kumar, N., & Obaidat, M. S. (2018, July). Blind signatures based secured e-healthcare system. In 2018 international conference on computer, information and telecommunication systems (CITS) (pp. 1–5). Washington, DC: IEEE.

    Google Scholar 

  57. Tanwar, S., Vora, J., Kaneriya, S., Tyagi, S., Kumar, N., Sharma, V., et al. (2019). Human arthritis analysis in fog computing environment using Bayesian network classifier and thread protocol. IEEE Consumer Electronics Magazine, 9(1), 88–94.

    Article  Google Scholar 

  58. Gupta, M., & Singla, N. (2019). Learner to advanced: Big data journey. In Handbook of IoT and big data (p. 187). Boca Raton, FL: CRC Press.

    Chapter  Google Scholar 

  59. 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 

  60. Tanwar, S., Patel, P., Patel, K., Tyagi, S., Kumar, N., & Obaidat, M. S. (2017, July). An advanced Internet of Thing based security alert system for smart home. In 2017 international conference on computer, information and telecommunication systems (CITS) (pp. 25–29). Washington, DC: IEEE.

    Chapter  Google Scholar 

  61. Yaqoob, I., Ahmed, E., Hashem, I. A. T., Ahmed, A. I. A., Gani, A., Imran, M., et al. (2017). Internet of things architecture: Recent advances, taxonomy, requirements, and open challenges. IEEE Wireless Communications, 24(3), 10–16.

    Article  Google Scholar 

  62. Scuotto, V., Ferraris, A., & Bresciani, S. (2016). Internet of Things: Applications and challenges in smart cities: A case study of IBM smart city projects. Business Process Management Journal, 22(2), 357–367.

    Article  Google Scholar 

  63. Tanwar, S., Obaidat, M. S., Tyagi, S., & Kumar, N. (2019). Online signature-based biometric recognition. In Biometric-based physical and cybersecurity systems (pp. 255–285). Cham: Springer.

    Chapter  Google Scholar 

  64. Tanwar, S., Tyagi, S., Kumar, N., & Obaidat, M. S. (2019). Ethical, legal, and social implications of biometric technologies. In Biometric-based physical and cybersecurity systems (pp. 535–569). Cham: Springer.

    Chapter  Google Scholar 

  65. Parikh, S., Dave, D., Patel, R., & Doshi, N. (2019). Security and privacy issues in cloud, fog and edge computing. Procedia Computer Science, 160, 734–739.

    Article  Google Scholar 

  66. Singh, S. P., Nayyar, A., Kumar, R., & Sharma, A. (2019). Fog computing: From architecture to edge computing and big data processing. The Journal of Supercomputing, 75(4), 2070–2105.

    Article  Google Scholar 

  67. Paul, A., Pinjari, H., Hong, W. H., Seo, H. C., & Rho, S. (2018). Fog computing-based IoT for health monitoring system. Journal of Sensors, 2018, 1–7.

    Article  Google Scholar 

  68. Vora, J., Tanwar, S., Tyagi, S., Kumar, N., & Rodrigues, J. J. (2017, October). 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) (pp. 1–6). Washington, DC: IEEE.

    Google Scholar 

  69. Stergiou, C., Psannis, K. E., Kim, B. G., & Gupta, B. (2018). Secure integration of IoT and cloud computing. Future Generation Computer Systems, 78, 964–975.

    Article  Google Scholar 

  70. Vatanparvar, K., Faruque, A., & Abdullah, M. (2015, April). Energy management as a service over fog computing platform. In Proceedings of the ACM/IEEE sixth international conference on cyber-physical systems (pp. 248–249). New York: ACM.

    Chapter  Google Scholar 

  71. Chen, E. T. (2017). The internet of things: Opportunities, issues, and challenges. In The internet of things in the modern business environment (pp. 167–187). Hershey, PA: IGI Global.

    Chapter  Google Scholar 

  72. Li, S., Da Xu, L., & Zhao, S. (2018). 5G Internet of Things: A survey. Journal of Industrial Information Integration, 10, 1–9.

    Article  Google Scholar 

  73. Lin, J., Yu, W., Zhang, N., Yang, X., Zhang, H., & Zhao, W. (2017). A survey on internet of things: Architecture, enabling technologies, security and privacy, and applications. IEEE Internet of Things Journal, 4(5), 1125–1142.

    Article  Google Scholar 

  74. Paul, P. V., & Saraswathi, R. (2017, March). The internet of things—A comprehensive survey. In 2017 international conference on computation of power, energy information and communication (ICCPEIC) (pp. 421–426). Washington, DC: IEEE.

    Google Scholar 

  75. Hosseinian-Far, A., Ramachandran, M., & Slack, C. L. (2018). Emerging trends in cloud computing, big data, fog computing, IoT and smart living. In Technology for smart futures (pp. 29–40). Cham: Springer.

    Chapter  Google Scholar 

  76. Dang, L. M., Hassan, S. I., Im, S., & Moon, H. (2019). Face image manipulation detection based on a convolutional neural network. Expert Systems with Applications, 129, 156–168.

    Article  Google Scholar 

  77. Dang, L. M., Hassan, S. I., Im, S., Mehmood, I., & Moon, H. (2018). Utilizing text recognition for the defects extraction in sewers CCTV inspection videos. Computers in Industry, 99, 96–109.

    Article  Google Scholar 

  78. Moscovice, I. S., & Rosenblatt, R. A. (1982). Rural health care delivery amidst federal retrenchment: Lessons from the Robert Wood Johnson Foundation’s Rural Practice Project. American Journal of Public Health, 72, 1380–1385.

    Article  Google Scholar 

  79. Pramanik, P. K. D., Nayyar, A., & Pareek, G. (2019). WBAN: Driving e-healthcare beyond telemedicine to remote health monitoring: Architecture and protocols. In Telemedicine technologies (pp. 89–119). Cambridge, MA: Academic Press.

    Chapter  Google Scholar 

  80. U.S. Congress, Office of Technology Assessment. Health Care in Rural America. Washington, DC: US Government Printing Office; 1990. Publication OTA-H-434.

    Google Scholar 

  81. Ermann, D. A. (1990). Rural health care: The future of the hospital. Medical Care Review, 47(1), 33–73.

    Article  Google Scholar 

  82. National Rural Health Association (US). Frontier Work Group and United States. Office of Rural Health Policy. (1994). Health care in frontier America: A time for change. USA: Office of Rural Health Policy, Health Resources and Services Administration, Public Health Service, US Department of Health and Human Services.

    Google Scholar 

  83. Prospective Payment Assessment Commission. (1991). Rural hospitals under Medicare’s prospective payment system (congressional report C-91-03). Washington, DC: US Government Printing Office.

    Google Scholar 

  84. Xu, Q., Ren, P., Song, H., & Du, Q. (2016). Security enhancement for IoT communications exposed to eavesdroppers with uncertain locations. IEEE Access, 4, 2840–2853.

    Article  Google Scholar 

  85. Gia, T. N., Jiang, M., Rahmani, A. M., Westerlund, T., Liljeberg, P., & Tenhunen, H. (2015, October). 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 (pp. 356–363). Washington, DC: IEEE.

    Chapter  Google Scholar 

  86. Tanwar, S., Tyagi, S., & Kumar, S. (2018). The role of internet of things and smart grid for the development of a smart city. In Intelligent communication and computational technologies (pp. 23–33). Singapore: Springer.

    Chapter  Google Scholar 

  87. Okay, F. Y., & Ozdemir, S. (2016, May). A fog computing based smart grid model. In 2016 international symposium on networks, computers and communications (ISNCC) (pp. 1–6). Washington, DC: IEEE.

    Google Scholar 

  88. Galli, S., Scaglione, A., & Wang, Z. (2011). For the grid and through the grid: The role of power line communications in the smart grid. Proceedings of the IEEE, 99(6), 998–1027.

    Article  Google Scholar 

  89. Verma, J. P., Tanwar, S., Garg, S., Gandhi, I., & Bachani, N. H. (2019). Evaluation of pattern based customized approach for stock market trend prediction with big data and machine learning techniques. International Journal of Business Analytics (IJBAN), 6(3), 1–15.

    Article  Google Scholar 

  90. Abdelwahab, S., Hamdaoui, B., Guizani, M., & Rayes, A. (2014). Enabling smart cloud services through remote sensing: An internet of everything enabler. IEEE Internet of Things Journal, 1(3), 276–288.

    Article  Google Scholar 

  91. Kaneriya, S., Tanwar, S., Nayyar, A., Verma, J. P., Tyagi, S., Kumar, N., et al. (2018, December). Data consumption-aware load forecasting scheme for smart grid systems. In 2018 IEEE Globecom workshops (GC Wkshps) (pp. 1–6). Washington, DC: IEEE.

    Google Scholar 

  92. Kumari, A., Tanwar, S., Tyagi, S., Kumar, N., Obaidat, M. S., & Rodrigues, J. J. (2019). Fog computing for smart grid systems in the 5G environment: Challenges and solutions. IEEE Wireless Communications, 26(3), 47–53.

    Article  Google Scholar 

  93. Kaneriya, S., Chudasama, M., Tanwar, S., Tyagi, S., Kumar, N., & Rodrigues, J. J. (2019, May). Markov decision-based recommender system for sleep apnea patients. In ICC 2019-2019 IEEE international conference on communications (ICC) (pp. 1–6). Washington, DC: IEEE.

    Google Scholar 

  94. ALzubi, J. A., Bharathikannan, B., Tanwar, S., Manikandan, R., Khanna, A., & Thaventhiran, C. (2019). Boosted neural network ensemble classification for lung cancer disease diagnosis. Applied Soft Computing, 80, 579–591.

    Article  Google Scholar 

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Jain, R., Gupta, M., Nayyar, A., Sharma, N. (2021). Adoption 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_1

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