Machine Learning Driven Edge Analytics for Healthcare: Problems, Difficulties, Future Directions, and Applications-A Review

Authors : Aafreen Qureshi; Dr. Gaurav Indra

Volume/Issue : Volume 7 - 2022, Issue 12 - December

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With the use of edge technology, cloud resources (particularly computing, storage, and network) will be made available in close proximity to edge devices, or smart gadgets where data is generated and consumed. Edge computing and edge analytics are two new ideas in edge technology that have emerged as a result of computer and application integration in edge devices. To examine the information produced through edge gadgets, edge analytics employs a number of methods or algorithms. The development of edge analytics has made the edge gadgets a whole set. Edge analytics is currently unable to fully accomodate the analytic methodologies. Due to several limitations like a low power supply, a tiny memory, a lack of resources, etc., the edge gadgets cannot conduct complex and refined analytic algorithms. The purpose of this paper is to give a thorough explanation of edge analytics. The following are the paper's main contributions: a detailed description of the differences among the three edge technology ideas of edge gadgets, edge computing, and edge analytics, as well as their problems. The article also examines how edge analytics are being used in numerous industries, including retail, agriculture, industry, and healthcare, to solve a variety of issues. Additionally, the research papers based on cutting-edge analytics are thoroughly examined in this article to analyse the current problems, new difficulties, research prospects, as well as utilizations.

Keywords : Edge Analytics, Edge Gadgets, Big Data, Sensor, Edge Computing, AI, ML, Health-Care.


Paper Submission Last Date
31 - March - 2023

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