Mathematical modelling for prediction of spread of corona virus and artificial intelligence/machine learning-based technique to detect COVID-19 via smartphone sensors Online publication date: Tue, 22-Nov-2022
by Sumeet Goyal; Digvijay Pandey; Harjinder Singh; Joginder Singh; Rahul Kakkar; P. Naga Srinivasu
International Journal of Modelling, Identification and Control (IJMIC), Vol. 41, No. 1/2, 2022
Abstract: COVID-19 is a novel corona virus which is infectious and communicable disease and it is originated from Wuhan, China. As the virus is mutating, the world is suffering from its spread again and again. However, the spread of communicable diseases can be predicted in advance so the proper preventive measures can be taken before it become life-taking. In this paper, mathematical model (SEIR) for the prediction of infectious diseases, which is modification of conventional SIR model is described and modelled which can be used to predict the cases in advance. A novel framework to detect COVID-19 from home is also proposed using artificial intelligence, machine learning and smartphone embedded sensors. The various smartphone embedded sensors such as proximity sensor, light sensor, accelerometer, gyroscope and fingerprint sensors are used to read the symptoms or activity and scan the CT images, and can be used to detect COVID-19.
Online publication date: Tue, 22-Nov-2022
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Modelling, Identification and Control (IJMIC):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email email@example.com