Article: COVID-19 detection and tracking using smart applications with artificial intelligence Journal: International Journal of Nanotechnology (IJNT) 2023 Vol.20 No.1/2/3/4 pp.433 - 449 Abstract: Corona Virus Disease 2019 (COVID-19), a newly identified pandemic infection, threatened human life, and disrupted the entire world. Identifying and detecting this pathogenic virus is made essential as it is increasing the mortality rate day by day. In this scenario, alternative technologies play a vital role in monitoring, detecting and diagnosing the disease by deploying smart applications. Today smart applications are incorporated with AI techniques in detecting and monitoring the spread of infection. The proposed work is contributed with multilayer perceptron (MLP) techniques integrating the artificial neural network (ANN) model for extracting COVID-19. The model is equipped with a normalisation process deploying Gaussian process regression (GPR) and radial based function (RBF) for detecting the noise level. The proposed work exploits the publicly available COVID-19 datasets of July month from GitHub and Kaggle. The AI model is measured using the performance metrics in terms of Precision, Recall, F-Measure and Accuracy and MLP model produces higher accuracy. Inderscience Publishers - linking academia, business and industry through research

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Title: COVID-19 detection and tracking using smart applications with artificial intelligence

Authors: Geeitha Senthilkumar; Rajagopal Kumar; C. Nalini; V.R. Niveditha; Jothilakshmi Ramakrishnan

Addresses: Department of Information Technology, M. Kumarasamy College of Engineering, Karur, Thalavapalayam, 639113, Tamil Nadu, India ' Department of Electronics and Instrumentation Engineering, National Institute of Technology, Chumkedima, Dimapur, Nagaland-797103, India ' Department of Information Technology, Kongu Engineering College, Perundurai, Erode-638 052, Tamil Nadu, India ' Department of Computer Science and Engineering, Sathyabama Institute of Science and Technology, Chennai, Tamil Nadu, India ' Department of Mathematics, Mazharul Uloom College Ambur, Ambur, 635802, Tamil Nadu, India Affiliated to Thiruvalluvar University, Tamil Nadu, India

Abstract: Corona Virus Disease 2019 (COVID-19), a newly identified pandemic infection, threatened human life, and disrupted the entire world. Identifying and detecting this pathogenic virus is made essential as it is increasing the mortality rate day by day. In this scenario, alternative technologies play a vital role in monitoring, detecting and diagnosing the disease by deploying smart applications. Today smart applications are incorporated with AI techniques in detecting and monitoring the spread of infection. The proposed work is contributed with multilayer perceptron (MLP) techniques integrating the artificial neural network (ANN) model for extracting COVID-19. The model is equipped with a normalisation process deploying Gaussian process regression (GPR) and radial based function (RBF) for detecting the noise level. The proposed work exploits the publicly available COVID-19 datasets of July month from GitHub and Kaggle. The AI model is measured using the performance metrics in terms of Precision, Recall, F-Measure and Accuracy and MLP model produces higher accuracy.

Keywords: COVID-19; smart applications; sensors; multilayer perceptron; multilayer perceptron; AI; artificial intelligence; detection.

DOI: 10.1504/IJNT.2023.131124

International Journal of Nanotechnology, 2023 Vol.20 No.1/2/3/4, pp.433 - 449

Received: 31 Aug 2021
Received in revised form: 08 Mar 2022
Accepted: 15 Mar 2022
Published online: 31 May 2023 *

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Title: COVID-19 detection and tracking using smart applications with artificial intelligence

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