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AFOROS: A Low-Cost Wi-Fi-Based Monitoring System for Estimating Occupancy of Public Spaces.

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Summary

This study introduces a Wi-Fi sensor system for real-time crowd estimation at events. By analyzing Wi-Fi probe requests and device fingerprints, it accurately counts attendees, enhancing venue management and security.

Keywords:
Wi-Fi probeWi-Fi sensorWi-Fi trackingautomatic people countingoccupancy estimationpassive tracking

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Data Science

Background:

  • Real-time crowd estimation is vital for venue security, management, and resource optimization.
  • Existing methods face challenges due to smartphone MAC address randomization.

Purpose of the Study:

  • To develop and validate a Wi-Fi sensor system for accurate, real-time crowd size estimation.
  • To overcome MAC address randomization for reliable device identification.

Main Methods:

  • Utilizing Wi-Fi sensor devices to capture and analyze probe request messages from smartphones.
  • Extracting unique device fingerprints from IEEE 802.11 frame information elements, bypassing MAC randomization.
  • Implementing algorithms to process Wi-Fi data for near real-time attendance estimation.

Main Results:

  • The system demonstrated high accuracy in estimating crowd numbers in real-world event scenarios.
  • Achieved an attendance estimation accuracy close to 95% in tested public events.
  • Successfully addressed the challenge posed by MAC address randomization in smartphones.

Conclusions:

  • The proposed Wi-Fi sensor system offers a reliable and accurate solution for real-time crowd estimation.
  • This technology can significantly improve security, management, and resource allocation in public venues.
  • The method provides a robust approach to device identification despite evolving privacy mechanisms in mobile devices.