Artificial Intelligence For Remote Patient Monitoring In IoTBased Healthcare Applications – An Overview

Abstract

Through m-Health and e-Health, a number of services are provided remotely, including avoiding
illnesses and treatment, evaluation of risk, medical monitoring, learning materials, and treatment. The popularity
of mobile health and electronic health care in society is due to this. For mobile health and electronic health, the
development of modern Internet of Things (IoT) devices and systems can be particularly beneficial. There are
several IoT electronic health care and mobile health designs that have been developed that can manage an
emergency situation well. However, traditional electronic health and mobile health systems don't use smartphone
sensors to gather and communicate crucial patient health data. In this study, we investigated m-Health and eHealth, which use body sensors and smartphone sensors to gather, analyse, and transmit client information
regarding health for standardized cloud storage. Patients and other participants may later be able to access the data
that has been kept. The findings of the current research revealed the trending classical machine learning models
in AI-based RPM, yet, with a note-worthy absence of the latest generation deep learning techniques such as
Transformers. The noted advantages of applying AI-based RPM include amongst others; enhancing medical care,
accelerating treatment, and lowering expenses. We have made suggestions for offer the AI, IoT and mobile
technologies that could be applied to achieve improved RPM solutions.