Data Analytics Using Machine Learning For Iot-Enabled Healthcare Systems

Abstract

One of the cutting-edge technologies that is gaining traction throughout the world is the Internet of Things. We can connect at any time, anywhere, and with any network or service because to the enormous power and capacity of IoT. The Internet of Things (IoT) is growing to be a powerhouse for next-generation machines, and its effects may be seen in the present corporate landscape. IoT is assisting businesses or researchers in the development of solutions. By integrating the current internet infrastructure for the efficient use of resources, they communicate with smart devices and smart objects. Additionally, it has the ability to expand services and advantages for intelligent systems. Beyond M2M (machine-to-machine) situations, the interests at stake include serial communication between the network and devices for delivering extreme services. An intelligent hybrid classification algorithm for an unbalanced ECG dataset based on the Internet of Things has been discussed in this study. The AD8232 heart rate sensor, the NodeMCU ESP32, and an intelligent hybrid classification algorithm for data categorization have been presented for an IoT-based ECG monitoring system.