Scopus Indexed Publications

Paper Details


Title
Towards COVID-19 Detection Information System Based on AIoT

Author
Md. Shamsuzzaman Miah, Abu Sufian, Ifat Hasan, Md. Atiqur Rahaman, Md. Jahidul Islam Ridoy, Touhid Bhuiyan,

Email

Abstract

An AIoT (Artificial Intelligence of Things) based COVID-19 detection system is a system that utilizes a combination of artificial intelligence (AI) and Internet of things (IoT) technologies to detect and diagnose individuals who have been infected with the COVID-19 virus. The system uses sensors to collect data on an individual's vital signs, such as heart rate, SPO2, temperature, and cough detection, which are considered typical symptoms of COVID-19. This data is then transmitted to a central hub or cloud-based platform, where it is analyzed by machine learning algorithms to determine if the individual has the virus. These algorithms are trained using large datasets of labeled patient data to detect COVID-19 by analyzing the vital signs mentioned above. Additionally, the AIoT system can also use other techniques such as computer vision for monitoring for symptoms like facial expression or voice analysis for coughs. The system provides real-time monitoring, alerting, and reporting capabilities. This makes it a useful tool for health organizations and governments to manage the spread of COVID-19, as well as provide fast, accurate, and non-invasive diagnostic tools. Our device will be small in size, easy to use, and easily accessible by anyone. We have used DC current to power this device; this device is small in size and powered by DC current, so it can be moved from one place to another without any hassle.


Keywords

Journal or Conference Name
Applied Intelligence for Healthcare Informatics: Techniques and Applications

Publication Year
2025

Indexing
scopus