4.6 Article

Edge Intelligence and Internet of Things in Healthcare: A Survey

Journal

IEEE ACCESS
Volume 9, Issue -, Pages 45-59

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2020.3045115

Keywords

Internet of Things; smart healthcare; artificial intelligence; edge computing; fog computing

Funding

  1. Deputyship for Research and Innovation, Ministry of Education, Saudi Arabia [IFKSURP-162]

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This study focuses on analyzing, understanding, and improving the architecture and technology of edge computing in smart healthcare to address the challenges of meeting individual health needs of patients, and explores the areas involving health data classification and artificial intelligence applications.
With the advent of new technologies and the fast pace of human life, patients today require a sophisticated and advanced smart healthcare framework that is tailored to suit their individual health requirements. Along with 5G and state-of-the-art smart Internet of Things (IoT) sensors, edge computing provides intelligent, real-time healthcare solutions that satisfy energy consumption and latency criteria. Earlier surveys on smart healthcare systems were centered on cloud and fog computing architectures, security, and authentication, and the types of sensors and devices used in edge computing frameworks. They did not focus on the healthcare IoT applications deployed within edge computing architectures. The first purpose of this study is to analyze the existing and evolving edge computing architectures and techniques for smart healthcare and recognize the demands and challenges of different application scenarios. We examine edge intelligence that targets health data classification with the tracking and identification of vital signs using state-of-the-art deep learning techniques. This study also presents a comprehensive analysis of the use of cutting-edge artificial intelligence-based classification and prediction techniques employed for edge intelligence. Even with its many advantages, edge intelligence poses challenges related to computational complexity and security. To offer a higher quality of life to patients, potential research recommendations for improving edge computing services for healthcare are identified in this study. This study also offers a brief overview of the general usage of IoT solutions in edge platforms for medical treatment and healthcare.

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