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Novel Face Mask Detection Technique using Machine Learning to control COVID'19 pandemic.

Sandeep Gupta1, S V N Sreenivasu2, Kuldeep Chouhan3

  • 1Department of Electrical Engineering, JECRC University, Jaipur, India.

Materials Today. Proceedings
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Summary

This study introduces a machine learning-powered mask detector to identify individuals not wearing face masks. This technology can enhance public health compliance in crowded areas.

Keywords:
AlexNetCOVID’19Corona virusDeep learningNeural networkSensor

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Area of Science:

  • Computer Science
  • Public Health
  • Machine Learning

Background:

  • The COVID-19 pandemic has caused widespread mortality and societal disruption.
  • Inadequate antiviral treatments and common transmission routes (breathing, coughing, sneezing) facilitate rapid virus spread.
  • Face masks are crucial personal protective equipment (PPE) for mitigating transmission, especially in public spaces.

Purpose of the Study:

  • To develop an automated system for detecting face mask usage.
  • To address the impracticality and cost of manual inspection for mask compliance.
  • To integrate a mask detection system with CCTV for enhanced public safety.

Main Methods:

  • Utilized a machine learning facial categorization system.
  • Developed a mask detector algorithm.
  • Designed for integration with existing Closed-Circuit Television (CCTV) infrastructure.

Main Results:

  • Successfully created a functional mask detection system.
  • The system accurately identifies individuals wearing or not wearing face masks.
  • The technology is suitable for real-time monitoring in public areas.

Conclusions:

  • Automated mask detection using machine learning offers a scalable solution for enforcing mask mandates.
  • This technology can improve compliance with public health guidelines.
  • Integration with CCTV systems provides a practical method for ensuring mask usage in high-traffic environments.