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Artificial intelligence-inspired comprehensive framework for Covid-19 outbreak control.

Munish Bhatia1, Ankush Manocha2, Tariq Ahamed Ahanger3

  • 1Department of Computer Science and Engineering, Lovely Professional University, India.

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|April 17, 2022
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Summary
This summary is machine-generated.

This study introduces an IoT framework using RFID and wearable sensors for remote COVID-19 patient surveillance. The system accurately identifies infection and tracks virus spread using fog-cloud analysis.

Keywords:
COVID-19Intelligent frameworkSelf organized mappingTemporal analysis

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Area of Science:

  • Medical Informatics
  • Epidemiology
  • Internet of Things (IoT)

Background:

  • COVID-19 poses a significant global health threat requiring continuous patient identification and remote monitoring.
  • Internet of Things (IoT) technology, integrated with fog-cloud computing, offers an efficient solution for real-time remote patient surveillance.

Purpose of the Study:

  • To propose a comprehensive framework for COVID-19 patient identification and management using IoT, RFID, and wearable sensors.
  • To leverage fog-cloud architecture for efficient and time-sensitive remote medical service delivery.
  • To assess the framework's performance in classifying infection severity and tracking disease spread.

Main Methods:

  • A fog-cloud framework integrating Radio Frequency Identification Device (RFID) and body-wearable sensors for patient monitoring.
  • Utilizing the J48 decision tree algorithm to assess infection degree based on user symptoms.
  • Employing RFID for detecting Temporal Proximity Interactions (TPI) and Temporal Network Analysis for tracking COVID-19 spread.

Main Results:

  • The proposed framework achieved high classification accuracy (96.68%) and sensitivity (94.65%) in statistical assessments.
  • Significant improvements were observed in Temporal Delay efficacy, Precision, and F-measure for the fog-cloud-based data analysis.
  • The system demonstrated effective performance in identifying infected individuals and analyzing disease transmission dynamics.

Conclusions:

  • The developed fog-cloud-based IoT framework provides an effective and accurate solution for remote COVID-19 patient surveillance and management.
  • The integration of RFID and wearable sensors, coupled with advanced analytical techniques, enhances the ability to monitor and control infectious disease outbreaks.
  • This approach offers a promising direction for improving public health responses to pandemics through technological innovation.