Improved Deep Neural Network Algorithm for Covid-19 Detection in Internet of Things

Articles in Press

Document Type : Original Article

Authors

1 1. Department of Computer Science, Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman,Kerman,Iran.

2 Department of Computer Science, Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman, Kerman, Iran.

Abstract

In this paper, we propose an automatic detection system of COVID-19 cases based on Internet of Things. In the proposed model, first, using Internet of Things technology, medical images are sent directly to the data collection after the suspicious person's visit through medical equipment equipped with Internet of Things, and then, in order to help radiologists to better interpret medical images, usage have been made of four pre-trained convolutional neural network models i.e. InceptionV3, InceptionResNetV2, VGG19 and ResNet152 as well as two datasets of chest radiology medical images and CT Scan in a 3-class classification for accurate prediction of cases suffering from COVID-19, healthy people, and diseased cases. Finally best result for CT- Scan images has been related to InceptionResNetV2 architecture with an accuracy of 99.366% and for radiology images related to the InceptionV3 architecture with an accuracy of 96.943%. The results show that this system leads to a reduction in daily visits to medical centers and thus reduces the pressure on the medical care system. It also helps rheology specialists to identify the disease as quickly as possible.

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Soft Computing Journal

Articles in Press, Accepted Manuscript
Available Online from 22 July 2023

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History

  • Receive Date: 12 December 2022
  • Revise Date: 05 July 2023
  • Accept Date: 22 July 2023

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