A Comprehensive Survey of the Internet of Things (IoT) and AI-Based Smart Healthcare

Fatima Alshehri,Ghulam Muhammad

doi:10.1109/access.2020.3047960

Fatima Alshehri, Ghulam Muhammad

Open Access

https://doi.org/10.1109/access.2020.3047960

Copy DOI

Abstract

Smart health care is an important aspect of connected living. Health care is one of the basic pillars of human need, and smart health care is projected to produce several billion dollars in revenue in the near future. There are several components of smart health care, including the Internet of Things (IoT), the Internet of Medical Things (IoMT), medical sensors, artificial intelligence (AI), edge computing, cloud computing, and next-generation wireless communication technology. Many papers in the literature deal with smart health care or health care in general. Here, we present a comprehensive survey of IoT- and IoMT-based edge-intelligent smart health care, mainly focusing on journal articles published between 2014 and 2020. We survey this literature by answering several research areas on IoT and IoMT, AI, edge and cloud computing, security, and medical signals fusion. We also address current research challenges and offer some future research directions.

Highlights

The rising number of chronic patients and the aging of the population render the avoidance of diseases an important requirement of healthcare
We present a detailed survey of Internet of Things (IoT)- and Internet of Medical Things (IoMT)-based smart health care systems
The proposed method was tested on a publicly available dataset called UTD-MHAD, and the results showed an improvement in overall classification rate (> 97%) compared to using each sensor separately

Summary

Introduction

The rising number of chronic patients and the aging of the population render the avoidance of diseases an important requirement of healthcare. Prevention is defined by regular exercise, nutrition, and periodic preventive controls as a way to sustain a healthier environment and as a method of keeping serious conditions from becoming worse. The future health sector must tackle an increasing number of chronic problems and the scarcity of treatments to satisfy patient demands [1]. COVID-19 has recently highlighted the importance of quick, comprehensive, and accurate eHealthcare and intelligent healthcare involving different types of medical and physiological data to diagnose the virus. The use of emerging technology in protective policies and behavioral systems can help identify potential health conditions early and enable the scheduling of appropriate steps, such as concurrently monitoring treatments and preparing new assessments. The world’s smart health market is forecast to reach USD 143.6 billion in 2019, which will expand by an average growth rate of 16.2% between 2020 and 2027 [2]

Objectives

Methods

Findings

Conclusion