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Mask Detection and Social Distance Identification Using Internet of Things and Faster R-CNN Algorithm.

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Summary

This study introduces a deep learning drone for real-time mask detection and social distancing enforcement. The automated system alerts individuals and authorities to ensure public health compliance.

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Area of Science:

  • Computer Vision
  • Artificial Intelligence
  • Public Health Technology

Background:

  • The COVID-19 pandemic highlighted the need for effective public health monitoring tools.
  • Traditional surveillance methods are often labor-intensive and lack real-time capabilities.
  • Unmanned systems offer a scalable solution for remote monitoring and compliance checks.

Purpose of the Study:

  • To design and implement a deep learning-enabled drone system for automated mask detection and social distancing monitoring.
  • To leverage the Industrial Internet of Things (IIoT) for real-time public health surveillance.
  • To develop an efficient system for alerting individuals and authorities about non-compliance.

Main Methods:

  • Utilized a Raspberry Pi 4 for drone automation and Industrial Internet of Things (IIoT) integration.
  • Implemented a Faster Regions with Convolutional Neural Network (Faster R-CNN) model for accurate face and mask detection.
  • Integrated an OpenCV camera for continuous image capture and analysis.
  • Developed an alert system using a speaker for immediate feedback to individuals and data transmission to authorities.

Main Results:

  • The system successfully detects unmasked individuals and those not maintaining social distance.
  • The Faster R-CNN model demonstrated high accuracy in face detection across various benchmark datasets.
  • Automated alerts were sent to non-compliant individuals and relevant authorities, including police stations.
  • The drone system provides 24/7 monitoring capabilities with daily reports.

Conclusions:

  • Deep learning-enabled drones offer a powerful tool for enforcing public health measures like mask-wearing and social distancing.
  • The integration of IIoT and Raspberry Pi 4 enables efficient, automated, and real-time monitoring solutions.
  • This technology can significantly enhance public safety and compliance in various settings.