View source for US Patent Application 18232975. Artificial Intelligence (AI)-Based Security Systems for Monitoring and Securing Physical Locations simplified abstract

=Artificial Intelligence (AI)-Based Security Systems for Monitoring and Securing Physical Locations=


==Organization Name==

[[:Category:BANK OF AMERICA CORPORATION|BANK OF AMERICA CORPORATION]]


[[Category:BANK OF AMERICA CORPORATION]]

==Inventor(s)==

[[:Category:George Anthony Albero of Charlotte NC (US)|George Anthony Albero of Charlotte NC (US)]][[Category:George Anthony Albero of Charlotte NC (US)]]

[[:Category:Nathalie Elizabeth Conley of Jacksonville FL (US)|Nathalie Elizabeth Conley of Jacksonville FL (US)]][[Category:Nathalie Elizabeth Conley of Jacksonville FL (US)]]

[[:Category:Elizabeth Jordan Knight of Clover SC (US)|Elizabeth Jordan Knight of Clover SC (US)]][[Category:Elizabeth Jordan Knight of Clover SC (US)]]

[[:Category:Lauren Thanh Nguyen-lo of Houston TX (US)|Lauren Thanh Nguyen-lo of Houston TX (US)]][[Category:Lauren Thanh Nguyen-lo of Houston TX (US)]]

[[:Category:Robert Jon Armstrong of Charlotte NC (US)|Robert Jon Armstrong of Charlotte NC (US)]][[Category:Robert Jon Armstrong of Charlotte NC (US)]]

==Artificial Intelligence (AI)-Based Security Systems for Monitoring and Securing Physical Locations - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18232975 titled 'Artificial Intelligence (AI)-Based Security Systems for Monitoring and Securing Physical Locations

==Simplified Explanation==

- The patent application is about monitoring a physical location to detect and predict anomalous activities.
- Machine learning algorithms are used to analyze inputs from various sensors, cameras, audio recording equipment, and other types of sensors.
- The purpose is to detect anomalous measurements or patterns.
- Notifications can be sent to devices in a network based on the detection of anomalies.


==Original Abstract Submitted==

Various aspects of the disclosure relate to monitoring a physical location to determine and/or predict anomalous activities. One or more machine learning algorithms may be used to analyze inputs from one or more sensors, cameras, audio recording equipment, and/or any other types of sensors to detect anomalous measurements/patterns. Notifications may be sent one or more devices in a network based on the detection.



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