Open Access

ARTICLE

A Detailed Study on IoT Platform for ECG Monitoring Using Transfer Learning

Md Saidul Islam^*

School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, 210044, Jiangsu, China

* Corresponding Author: Md Saidul Islam. Email:

Journal on Internet of Things 2022, 4(3), 127-140. https://doi.org/10.32604/jiot.2022.037489

Received 05 November 2022; Accepted 07 March 2023; Issue published 12 June 2023

Abstract

Internet of Things (IoT) technologies used in health have the potential to address systemic difficulties by offering tools for cost reduction while improving diagnostic and treatment efficiency. Numerous works on this subject focus on clarifying the constructs and interfaces between various components of an IoT platform, such as knowledge generation via smart sensors collecting biosignals from the human body and processing them via data mining and, in recent times, deep neural networks offered to host on cloud computing architecture. These approaches are intended to assist healthcare professionals in their daily activities. In this comparative research, we discuss the construction of an IoT network for real-time management and monitoring of a network of biosensors and gateways and the utilization of a cloud-based deep neural network architecture with such categorization of ECG data into various cardiovascular diseases. The aim of this paper is to provide a quicker transmission of data at a cheaper rate.

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Keywords

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