Scopus Indexed Publications

Paper Details


Title
IoT based Health Monitoring Automated Predictive System to Confront COVID-19
Author
, Maksudur Rahman,
Email
Abstract
As the whole world is striving to combat the Coronavirus disease (COVID-19), healthcare and health monitoring systems are struggling to confront the virus. Many cases have been observed where the COVID-19 could not be identified at a specific time. Furthermore, any effective strategy that can monitor the coronavirus state in the human body has not been established yet. As a result, patients of the coronavirus could not receive proper treatment when necessary. Therefore, the death toll due to COVID-19 is rising. This paper proposes a systematic approach to combat the COVID-19 pandemic more efficiently by combining the concept of ‘Internet of Things’ (IoT) and machine learning (ML). The paper also gives a brief idea about how IoT can be used to monitor the health status and also to detect the severity of coronavirus in a human body by using some of the biological data such as body temperature, heart pulse, etc. from the patient's body. The developed system can provide healthcare, maintain distant communication, and emergency medical support to the patients. This paper proposes a practical solution with the help of the developed health monitoring system that can mitigate the loss done by the COVID-19.

Keywords
COVID-19 , IoT , Machine Learning , Embedded Multiple Sensors , Health Monitoring System , IoMT
Journal or Conference Name
2020 IEEE 17th International Conference on Smart Communities: Improving Quality of Life Using ICT, IoT and AI (HONET)
Publication Year
2020
Indexing
scopus