AIoT Based COVID-19 Detection System

AIoT Based COVID-19 Detection System

Md. Shamsuzzaman Miah, Abu Sufiun, Eng. Golam Rabbany, Ifat Hasan and Md. Jahidul Islam Ridoy

Department of Computer Science and Engineering, Daffodil International University, Dhaka, BANGLADESH Corresponding author: shamsuzzamancse.fab@daffodilvarsity.edu.bd

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, Sop2, temperature, and cough detection which are considered as 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 providing fast, accurate and non-invasive diagnostic tool. Our device will be small in size, easy to use, 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.