IP Library › Granted Patent US 12,494,059
Granted Patent B2
US 12,494,059 · App. 18/121,348 · Granted Dec 9, 2025

Electric power grid inspection and management system

Inventors: Kunal Datta (San Francisco, CA); Tony Chen (San Francisco, CA); Marcella Kwan (San Francisco, CA); Patrick Buckles (San Ramon, CA); Michael James Locatelli (Pittsburg, CA); Teresa Alapat (Walnut Creek, CA); Maria Joseph (San Francisco, CA); Michael S. Glass (Oakland, CA); Jonathan Mello (El Cerrito, CA); Khushar Faizan (Walnut Creek, CA); Xiwang Li (El Cerrito, CA); Michael Signorotti (Los Angeles, CA); Guilherme Mattar Bastos (San Francisco, CA); Jacinto Chen (San Francisco, CA); Erin Melissa Tan Antono (San Francisco, CA); David Grayson (Portland, OR); Jeffrey Mark Lovington (Santa Rosa, CA); Laura Fehr (Walnut Creek, CA); Charlene Chi-Johnston (San Francisco, CA)
Assignee: PACIFIC GAS AND ELECTRIC COMPANY
G06V20/41G06V20/17
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Quick Facts
Patent No.
US 12,494,059
App. No.
18/121,348
Granted
Dec 9, 2025
Kind
B2
Abstract

In some embodiments, the system is directed to an autonomous inspection system for electrical grid components. In some embodiments, the system collects electrical grid component data using an autonomous drone and then transmits the inspection data to one or more computers. In some embodiments, the system includes artificial intelligence that analysis the data and identifies electrical grid components defects and provides a model highlighting the defects to a user. In some embodiments, the system enables a user to train the artificial intelligence by providing feedback for models where defects or components are not properly identified.

Claims (32)

1 . An electric power grid inspection and management system comprising:

one or more computers comprising one or more processors and one or more non-transitory computer readable media, the one or more non-transitory computer readable media comprising instructions stored thereon that when executed configure the one or more computers to:

generate, by the one or more processors, an inspection interface equipped to enable a user to notate one or more images and generate one or more inspection reports about one or more electrical grid components;

receive, by the one or more processors, inspection data from one or more inspection devices, the inspection data including the one or more images, the one or more images each comprising one or more electrical grid components;

notate, by the one or more processors, the one or more electrical grid components in the inspection data using artificial intelligence (AI);

receive, by the one or more processors, a user submitted inspection report from the inspection interface comprising the one or more AI notated electrical grid components; and

send, by the one or more processors, the inspection report to the AI as training data;

wherein the system is configured to use a plurality of historical inspection reports generated by the inspection interface for a structure as prediction training for the same structure.

2 . The electric power grid inspection and management system of claim 1 ,

wherein the inspection report includes at least one unchanged artificial intelligence notation.

3 . The electric power grid inspection and management system of claim 2 ,

wherein the AI is further equipped to automatically provide a description of defect issues associated with the one or more electrical grid components in the inspection interface.

4 . The electric power grid inspection and management system of claim 3 ,

wherein the description includes one or more of an image file name, an electrical grid component description, an electrical grid component structure label, an electrical grid component equipment identification, and/or an electrical grid component geographical position of the one or more electrical grid components in the inspection interface.

5 . The electric power grid inspection and management system of claim 3 ,

wherein the AI is used to automatically provide the description; and

wherein automatically providing the description includes the AI using the inspection report as training data.

6 . The electric power grid inspection and management system of claim 5 ,

wherein the training data comprises one or more electrical grid component images and/or descriptions including one or more of heart rot, damaged conductors, insulators, overgrown vegetation, and/or hooks.

7 . The electric power grid inspection and management system of claim 1 ,

wherein the AI is equipped to filter the one or more images.

8 . The electric power grid inspection and management system of claim 1 ,

wherein the inspection report includes a user change to an AI notation.

9 . The electric power grid inspection and management system of claim 8 ,

wherein the AI is equipped to use the user change to the AI notation as an indication of an incorrect notation.

10 . The electric power grid inspection and management system of claim 9 ,

wherein the AI is equipped to use the user change as an indication of a correct notation.

11 . The electric power grid inspection and management system of claim 1 , wherein the AI is equipped to analyze at least one of the plurality of historical inspection reports.

12 . The electric power grid inspection and management system of claim 11 , wherein the AI is equipped to identify defects not identified by a user in the plurality of historical inspection reports.

13 . The electric power grid inspection and management system of claim 11 , wherein the AI is equipped to identify defects not identified previously by the AI in the plurality of historical inspection reports.

14 . The electric power grid inspection and management system of claim 11 ,

wherein the one or more images are received via a drone camera.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 14, 2025
From: SIGNOROTTI, MICHAEL; BASTOS, GUILHERME MATTAR; CHEN, JACINTO; TAN ANTONO, ERIN MELISSA; GRAYSON, DAVID; LOVINGTON, JEFFREY MARK; FEHR, LAURA; CHI-JOHNSTON, CHARLENE
To: PACIFIC GAS AND ELECTRIC COMPANY
Reel/Frame 069853/0164 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 6, 2024
From: DATTA, KUNAL; CHEN, TONY; KWAN, MARCELLA; BUCKLES, PATRICK; LOCATELLI, MICHAEL JAMES; ALAPAT, TERESA; JOSEPH, MARIA; GLASS, MICHAEL S.; MELLO, JONATHAN; FAIZAN, KHUSHAR; LI, XIWANG
To: PACIFIC GAS AND ELECTRIC COMPANY
Reel/Frame 069160/0515 →
Continuity (3)
Continuation In Part 16942060 · Jul 29, 2020
Provisional Application 62880043 · Jul 29, 2019
Related Publication 20230222793A1 · Jul 13, 2023
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