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A low-cost sensor based smart and efficient health monitoring system for elderly people using internet of things

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BRAC University

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Abstract

A smart and connected healthcare system is one of the most popular applications enabled by the Internet of Things (IoT). It is possible to get a rich informative indication of our physical health using networked sensors either worn or embedded in our living environments. As the aging population is constantly rising both in rural and urban areas, there is a need for an IoT-based health monitoring system to continuously monitor their health. As a result, visits to the doctors for a regular check-up is minimized and doctors can save many lives by providing valuable services in emergency purpose. In this research, a progressive method for IoT-based health monitoring system has been proposed. An architecture customized for healthcare applications is proposed and implemented as a prototype. The proposed system collects data from a patient’s body using different sensors such as an ECG sensor, Pulse Oximeter sensor, and Temperature Sensor and sends it to the cloud where it is processed and analyzed. A video surveillance camera has also been used here to continuously monitor a patients’ movement. In this study, a system is designed to frequently monitor the ECG signal, blood oxygen level, temperature, heart rate from the patient’s body using wearable sensors, and the data is stored in the database which can be accessed by authorized personnel only. When any abnormalities are found in a patients’ body an automatic email has been sent to the users and doctors for analyzing the critical conditions of the patients and provides emergency health assistance. The prototype of the proposed system for remote health monitoring has been built to demonstrate its performance advantages and the result shows that the system is efficient for remote health monitoring. It can be invoked from a remote location and in any case of abnormalities found in the patient’s body an emergency email will be sent automatically to the authorized doctors and users.

Description

Cataloged from PDF version of thesis.
Includes bibliographical references (pages 80-89).
This thesis is submitted in partial fulfilment of the requirements for the degree of Master of Science in Electrical and Electronic Engineering, 2020.

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Thesis