IP Library Granted Patent US 12,475,321
Granted Patent B2
US 12,475,321 · App. 18/337,966 · Granted Nov 18, 2025

Analyzing monitoring system events using natural language processing (NLP)

Inventors: Bhaskar Thadisetty (Boca Raton, FL); Patrick Black (Portland, CT); Connor Mcnaboe (Burlington, CT); Gary Friar (Sebring, FL)
Assignee: The ADT Security Corporation
G06F40/30G10L15/1815G10L15/22G10L25/63
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Quick Facts
Patent No.
US 12,475,321
App. No.
18/337,966
Filed
Jun 20, 2023
Granted
Nov 18, 2025
Kind
B2
Examiner
YEN, ERIC L
Art Unit
2658
USPC
704/9
Abstract

A language device is described. A language device includes processing circuitry configured to: determine an urgency level of a message based at least in part on a natural language processing (NLP) model; determine a priority of an event associated with the message based at least in part on the urgency level; and order the message relative to a plurality of other messages in a customer queue based at least in part on the priority of the event associated with the message.

Claims (15)

1 . A system, comprising:

at least one processor; and

at least one computer-readable storage medium comprising a plurality of instructions that, when executed by the at least one processor, cause the at least one processor to:

determine an urgency level for a message by at least inputting data associated with the message into a natural language processing (NLP) model;

order the message relative to a plurality of other messages in a customer queue based at least in part on the urgency level for the message;

determine a resolution type based at least in part on the message;

retrain the NLP model based at least in part on the resolution type;

determine an alert to be transmitted to a first responder based at least in part on the NLP model;

determine a plurality of messages associated with the message;

input the plurality of messages to another NLP model to determine:

a performance level of an agent associated with at least one of the plurality of messages; and

an effectiveness level of an event disposition;

determine an NLP model update based on the event disposition;

input voice data associated with a voice call to the another NLP model to prioritize the voice call, the another NLP model being configured to detect an emotion of a person associated with the voice data; and

cause transmission of the message to at least one agent device of a plurality of agent devices, the at least one agent device being selected based on the NLP model.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 29, 2023
From: THADISETTY, BHASKAR; BLACK, PATRICK; MCNABOE, CONNOR; FRIAR, GARY
To: THE ADT SECURITY CORPORATION
Reel/Frame 064117/0706 →
Continuity (3)
Continuation 18066761 · Dec 15, 2022
Provisional Application 63292245 · Dec 21, 2021
Related Publication 20230334258A1 · Oct 19, 2023
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