Smart IOT Based Healthcare Monitoring and Decision-Making System Using Augmented Data Recognition Algorithm

Abstract

Many medical errors occur because people are in charge of patients or elderly medications by handling large amounts of medications every day. This work consists of designing and establishing a pillbox prototype intended to address this shortcoming in medical areas. It can be used separately from the medication itself and other advanced features provided with this device by the hospital or retirement home. This medication pack aims to take most medications or vitamin supplements or stimulants that deal with over-salting or over-the-counter patients. The proposed smart pillbox contains a program that enables medical caregivers or clients to determine the pill size and timing of pills and service routine each day. In this research work, the Augmented Data Recognition (ADR) algorithm is also used to monitor humans' health conditions. Initially, the UCI dataset is used for training and validation of the proposed ADR algorithm. The heart rate, blood pressure and temperature of the patient have carried during the testing phase via the Internet of Things (IoT) setup. The testing phase estimates any abnormalities in the health status based on the information obtained by the sensor collected by the population structure. Statistical analysis is based on data obtained from a cumulative cloud from IoT devices to estimate percentage accuracy.

A Novel Scheme for Classification of Epilepsy Using Machine Learning and a Fuzzy Inference System Based on Wearable-Sensor Health Parameters

“…Internet of Medical Things (IoMT)-based healthcare monitoring systems have been suggested, developed, and subjected to fuzzy logic-based artificial intelligence analysis [13]. A low-cost, high-quality, versatile, wearable smart device was designed to track fitness athletes and patients with heart disorders in the healthcare system [14]. An innovative and intelligent healthcare system has been created based on cutting-edge innovations like ML and the Internet of Things (IoT) [13,15].…”