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US Patent 11361637 Gunshot detection system with ambient noise modeling and monitoring

Patent 11361637 was granted and assigned to Johnson Controls on June, 2022 by the United States Patent and Trademark Office.

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Is a
Patent
Patent
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Patent attributes

Current Assignee
Johnson Controls
Johnson Controls
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Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
113616370
Patent Inventor Names
Alan Levin, III0
Thomas Wysong Connell, II0
Date of Patent
June 14, 2022
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Patent Application Number
169689370
Date Filed
February 14, 2019
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Patent Citations
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US Patent 10102732 Danger monitoring system
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US Patent 10657800 Gunshot detection within an indoor environment
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US Patent 10586109 Indoor gunshot detection with video analytics
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US Patent 10741058 Visual lockdown notification and alert device, electronic door stop remote broadcast device, silent broadcast signal-activated electronic door stop, and sound-activated remote release electronic door stop
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US Patent 11282536 Systems and methods for detecting a gunshot
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US Patent 10928244 Detection of discharge of projectile from firearm
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US Patent 10089845 System and method of detecting and analyzing a threat in a confined environment
Patent Primary Examiner
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John A. Tweel, Jr.
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CPC Code
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G08B 13/1672
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G08B 17/00
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A gunshot detection system continually monitors ambient noise throughout a building, learns the building's auditory patterns, and alerts users when sounds are found to be unusual or generally indicative of a dangerous situation. For example, gunshot sensor units positioned throughout the building include microphones. During a learning period (e.g. during normal conditions), these microphones capture ambient noise. The gunshot detection system generates ambient noise models representing the ambient noise during the normal conditions. The gunshot detection system then continually processes currently captured audio data depicting ambient noise (and potential acoustic anomalies) against the ambient noise models to detect and/or identify the acoustic anomalies and to determine whether to generate an alert.

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