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Healthcare 4.0: A Voyage of Fog Computing with IOT, Cloud Computing, Big Data, and Machine Learning

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Fog Computing for Healthcare 4.0 Environments

Abstract

The healthcare industry has come a long way with a series of revolutions starting from Healthcare 1.0 up to Healthcare 4.0 where innovation made efforts to save human lives better than the past. Today IoT devices around the world and especially in healthcare domain generate a huge amount of data with 3Vs of big data, i.e., velocity, variety, and volume. This is where fog computing and cloud computing have come up in utilizing those data which can be utilized for analytics and modeling purposes which can keep records as well as predict the patients’ health by performing analysis. In the age of IoT and AI, which is bringing amazing possibilities and intelligence in various industries, it has brought revolutions in healthcare as well by giving real-time analytics on patient’s data without fail with help of fog computing and cloud computing. In this chapter, the role of IoT, fog computing, and cloud computing has been described along with applications of machine learning and big data that runs on these paradigms has been explained. Issues related to cloud computing and motivation behind bringing fog computing paradigm have also been explained in detail. Several architectures of fog computing are also discussed in this chapter along with their application and comparison. Application of big data and machine learning modeling has also been explained in later part of the chapter. Lastly, case studies related to fog computing, big data, and machine learning in healthcare has been explained and compared.

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Correspondence to Ambarish Gajendra Mohapatra .

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Sarangi, A.K., Mohapatra, A.G., Mishra, T.C., Keswani, B. (2021). Healthcare 4.0: A Voyage of Fog Computing with IOT, Cloud Computing, Big Data, and Machine Learning. 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_8

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  • DOI: https://doi.org/10.1007/978-3-030-46197-3_8

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