17644363. ACOUSTIC ANALYSIS OF CROWD SOUNDS simplified abstract (INTERNATIONAL BUSINESS MACHINES CORPORATION)

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ACOUSTIC ANALYSIS OF CROWD SOUNDS

Organization Name

INTERNATIONAL BUSINESS MACHINES CORPORATION

Inventor(s)

Rachel Ostrand of Milford PA (US)

Vagner Figueredo De Santana of Sao Paulo (BR)

Alecio Pedro Delazari Binotto of Munich (BR)

ACOUSTIC ANALYSIS OF CROWD SOUNDS - A simplified explanation of the abstract

This abstract first appeared for US patent application 17644363 titled 'ACOUSTIC ANALYSIS OF CROWD SOUNDS

Simplified Explanation

The patent application describes a method, computer system, and computer program for detecting face mask usage based on crowd sound. Here is a simplified explanation of the abstract:

  • The invention captures an audio stream that includes crowd voice data.
  • It analyzes the crowd voice data using a machine learning model to determine the number of people wearing masks.
  • If the number of people wearing masks is below a certain compliance threshold, the invention displays content to promote face mask usage.

Potential applications of this technology:

  • Public health monitoring: The technology can be used in public spaces like airports, train stations, or shopping malls to monitor compliance with face mask usage and take appropriate actions to promote safety.
  • Event management: It can be employed in large gatherings or events to ensure that attendees are following face mask guidelines and to provide reminders if necessary.
  • Workplace safety: The technology can be implemented in offices or factories to monitor employee compliance with face mask policies and encourage adherence.

Problems solved by this technology:

  • Monitoring compliance: The technology provides a way to automatically monitor the usage of face masks in crowded areas, eliminating the need for manual checks.
  • Prompting action: By displaying content to promote face mask usage, the technology encourages individuals to wear masks and helps create a safer environment.

Benefits of this technology:

  • Efficiency: The automated detection and analysis of face mask usage based on crowd sound saves time and resources compared to manual monitoring.
  • Real-time feedback: The technology provides immediate feedback on compliance levels, allowing for timely interventions if necessary.
  • Promoting safety: By displaying content to promote face mask usage, the technology helps create awareness and encourages individuals to follow guidelines, contributing to public health and safety.


Original Abstract Submitted

A method, computer system, and a computer program product for detecting face mask usage based on a crowd sound is provided. The present invention may include capturing an audio stream including a crowd voice data. The present invention may also include analyzing the crowd voice data using a machine learning model to determine an amount of people wearing masks. The present invention may further include in response to determining that the amount of people wearing masks does not meet a compliance threshold, displaying a content to promote face mask usage.

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