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Automation Monitoring With Sensors For Detecting Covid Using Backpropagation Algorithm

Pravin R. Kshirsagar, Hariprasath Manoharan, Vineet Tirth, Mohd Naved, Ahmad Tasnim Siddiqui, Arvind Kumar Sharma

2021KSII Transactions on Internet and Information Systems17 citationsDOIOpen Access PDF

Abstract

This article focuses on providing remedial solutions for COVID disease through the data collection process. Recently, In India, sudden human losses are happening due to the spread of infectious viruses. All people are not able to differentiate the number of affected people and their locations. Therefore, the proposed method integrates robotic technology for monitoring the health condition of different people. If any individual is affected by infectious disease, then data will be collected and within a short span of time, it will be reported to the control center. Once, the information is collected, then all individuals can access the same using an application platform. The application platform will be developed based on certain parametric values, where the location of each individual will be retained. For precise application development, the parametric values related to the identification process such as sub-interval points and intensity of detection should be established. Therefore, to check the effectiveness of the proposed robotic technology, an online monitoring system is employed where the output is realized using MATLAB. From simulated values, it is observed that the proposed method outperforms the existing method in terms of data quality with an observed percentage of 82.

Topics & Concepts

Computer scienceBackpropagationAutomationCoronavirus disease 2019 (COVID-19)Artificial intelligenceAlgorithmMachine learningData miningArtificial neural networkMedicineEngineeringMechanical engineeringDiseaseInfectious disease (medical specialty)PathologyCOVID-19 diagnosis using AICOVID-19 epidemiological studies
Automation Monitoring With Sensors For Detecting Covid Using Backpropagation Algorithm | Litcius