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AI-assisted Emergency Healthcare using Vehicular Network and Support Vector Machine.

Biswa Ranjan Senapati¹, Pabitra Mohan Khilar^1,2, Tirtharaj Dash^3,4

¹Present Address: Department of CSE, ITER, Siksha 'O' Anusandhan (Deemed to be University), Bhubaneswar, India.

Wireless Personal Communications

|May 19, 2023

Summary

This study introduces an automated system for monitoring individuals in quarantine centers during the COVID-19 pandemic. The novel method enhances health data transmission and analysis, achieving 96.8% accuracy in risk classification.

Keywords:

Delay NIB Support vector machine VANET

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Area of Science:

Computer Science
Public Health
Network Engineering

Background:

The COVID-19 pandemic necessitates effective quarantine strategies.
Current quarantine monitoring methods are insufficient, leading to staff infections and rising cases.
Automated monitoring is crucial for managing quarantine centers efficiently and safely.

Purpose of the Study:

To propose a novel, automated two-phase system for monitoring individuals in quarantine centers.
To improve the efficiency and safety of quarantine management through technology.
To reduce the risk of infection among healthcare workers and quarantine personnel.

Main Methods:

A geographic-based routing protocol for health data transmission, considering factors like density, shortest path, and delay.
Utilizing components such as Network-in-box, Roadside-units, and vehicles for data routing.
A health data analysis phase employing a support vector machine (SVM) for multi-class classification of health status (normal, low, medium, high-risk).

Main Results:

The proposed geographic-based routing outperforms existing methods in terms of End-to-End (E2E) delay, network gaps, and packet delivery ratio.
The support vector machine (SVM) achieved an overall testing accuracy of 96.8% in classifying health data into four risk categories.
The system demonstrated significant improvements in data transmission and health risk analysis.

Conclusions:

The proposed automated monitoring system offers a practical and effective solution for quarantine centers.
The system enhances the safety of both quarantined individuals and healthcare staff.
The high accuracy in health data analysis shows strong potential for real-world adoption in pandemic management.