IP Library Granted Patent US 12,499,333
Granted Patent B1
US 12,499,333 · App. 19/047,339 · Granted Dec 16, 2025

Autonomous journalism with artificial intelligence and sensory data processing

Inventor: Jeffrey Don Crump (Mesa, AZ)
Assignee: NewsGenie, Inc.
G06F40/58G06F40/30G06Q30/0246G06V40/172G10L13/027G10L13/047
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Quick Facts
Patent No.
US 12,499,333
App. No.
19/047,339
Granted
Dec 16, 2025
Kind
B1
Abstract

Methods, systems, and devices for autonomous journalism with artificial intelligence and sensory data processing are described. In some examples, a server may receive real-time sensory data from various sources related to a news event. The server may process this data to create a structured news report by utilizing natural language processing and machine learning algorithms, which contextualize and verify the factual content of the news event. An autonomous reporting agent may be dispatched to the event's location in response to the processed sensory data. The server may then generate a dynamic news update that incorporates the autonomous agent's reporting and the structured news report, providing real-time, adaptive news coverage.

Claims (42)

1 . A method for autonomous journalism with drones, artificial intelligence, and data processing, comprising:

receiving, by a server, real-time event data from a plurality of sources associated with a news event, the plurality of sources including social media feeds;

processing, by the server, the real-time event data to generate a structured news report, the processing including applying natural language processing to interpret sentiment and tone of the real-time event data, and applying machine learning algorithms trained on a dataset of historical news events to contextualize and verify factual content of the news event based on identification of entities and events within the real-time event data;

dispatching, by the server, an autonomously-controlled flying drone equipped with cameras and sensors to a location of the news event in response to the processing of the real-time event data;

generating, by the drone, reports of the news event;

obtaining, by the server from the drone, the reports of the news event; and

generating, by the server, a dynamic news update based on the reports obtained from the drone and the structured news report.

2 . The method of claim 1 , further comprising cross-referencing, by the server, the factual content with additional databases to enhance an accuracy of the structured news report in response to detecting inconsistencies in the real-time event data.

3 . The method of claim 1 , further comprising adapting, by the server, a tone and depth of the dynamic news update based on real-time audience engagement metrics collected during dissemination of the structured news report.

4 . The method of claim 1 , further comprising synthesizing, by the server, speech and gestures for an AI-generated avatar to deliver the dynamic news update in a studio setting, in response to the structured news report being finalized.

5 . The method of claim 1 , further comprising translating, by the server, the dynamic news update into multiple languages for simultaneous distribution across various media platforms in response to predefined user preferences.

6 . The method of claim 1 , further comprising deploying, by the server, additional drones equipped with environmental sensors to the location of the news event in response to the drone's initial assessment.

7 . The method of claim 1 , further comprising,

dispatching an autonomous drone journalist equipped with a camera to provide aerial coverage of the location; and

capturing, by the autonomous drone journalist, live video footage for inclusion in the structured news report.

8 . The method of claim 1 , further comprising generating a personalized news update tailored to a user's preferences by analyzing the user's previous interactions with news content.

9 . The method of claim 1 , further comprising integrating real-time interactive Q&A capabilities into the structured news report, allowing live audience members to submit questions and receive immediate, AI-generated responses related to news content.

10 . The method of claim 1 , wherein the drone is configured with facial recognition software to identify and interview individuals at the news event for inclusion in the dynamic news update.

11 . The method of claim 1 , wherein the server applies sentiment analysis to the real-time event data to determine an emotional tone of the news event and adjust a presentation style of the dynamic news update accordingly.

12 . The method of claim 1 , wherein the server archives the structured news report with metadata tagging for searchability and retrieval in future news aggregation and synthesis.

13 . The method of claim 1 , wherein the server coordinates movements of the drone with local authorities to ensure compliance with regulations and safety protocols.

14 . A system configured for autonomous journalism with drones artificial intelligence, and data processing, comprising:

an autonomously-controlled flying drone equipped with cameras and sensors;

a processor;

memory coupled with the processor; and

instructions stored in the memory and executable by the processor to cause the system to:

receive real-time event data from a plurality of sources associated with a news event, the plurality of sources including social media feeds;

process the real-time event data to generate a structured news report by applying natural language processing to interpret sentiment and tone of the real-time event data, and applying machine learning algorithms trained on a dataset of historical news events to contextualize and verify factual content of the news event based on identification of entities and events within the real-time event data;

dispatch the drone to a location of the news event in response to processing the real-time event data; and

obtain, by the server from the drone, reports of the news event generated by the drone; and

generate a dynamic news update based on the reports from the drone and the structured news report.

15 . The system of claim 14 , wherein the instructions are further executable by the processor to cause the system to: cross-reference the factual content with additional databases to enhance an accuracy of the structured news report in response to detecting inconsistencies in the real-time event data.

16 . The system of claim 14 , wherein the instructions are further executable by the processor to cause the system to: adapt a tone and depth of the dynamic news update based on real-time audience engagement metrics collected during dissemination of the structured news report.

17 . The system of claim 14 , wherein the instructions are further executable by the processor to cause the system to: synthesize speech and gestures for an AI-generated avatar to deliver the dynamic news update in a studio setting, in response to the structured news report being finalized.

18 . The system of claim 14 , wherein the instructions are further executable by the processor to cause the system to: translate the dynamic news update into multiple languages for simultaneous distribution across various media platforms in response to predefined user preferences.

19 . The system of claim 14 , wherein the instructions are further executable by the processor to cause the system to: deploy additional drones equipped with environmental sensors to the location of the news event in response to the drone's initial assessment.

20 . A non-transitory computer-readable medium storing code for autonomous journalism with drones, artificial intelligence, and data processing, the code comprising instructions executable by a processor to:

receive real-time event data from a plurality of sources associated with a news event, the plurality of sources including social media feeds;

process the real-time event data to generate a structured news report by applying natural language processing to interpret sentiment and tone of the real-time event data, and applying machine learning algorithms trained on a dataset of historical news events to contextualize and verify factual content of the news event based on identification of entities and events within the real-time event data;

dispatch an autonomously-controlled flying drone equipped with cameras and sensors to a location of the news event in response to processing the real-time event data; and

obtain, by the server from the drone, reports of the news event generated by the drone; and

generate a dynamic news update based on the reports obtained from the drone and the structured news report.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 6, 2025
From: CRUMP, JEFFREY DON
To: NEWSGENIE, INC.
Reel/Frame 070136/0284 →
References Cited (12)
US 6301579B1 · Becker · 2001 [cited by examiner]
US 11977854B2 · Tunstall-Pedoe · 2024 [cited by examiner]
US 12231380B1 · Rodgers · 2025 [cited by examiner]
US 20020059069A1 · Hsu · 2002 [cited by examiner]
US 20170270805A1 · Parker · 2017 [cited by examiner]
US 20170351962A1 · Appel · 2017 [cited by examiner]
US 20200226133A1 · Li · 2020 [cited by examiner]
US 20210286635A1 · Swvigaradoss · 2021 [cited by examiner]
US 20230360519A1 · Sudhir · 2023 [cited by examiner]
US 20240070899A1 · Wagner · 2024 [cited by examiner]
US 20240236018A1 · Eldering · 2024 [cited by examiner]
US 20250006182A1 · Ingel · 2025 [cited by examiner]