IP Library Granted Patent US 12,248,489
Granted Patent B2
US 12,248,489 · App. 18/537,610 · Granted Mar 11, 2025

Intelligent data contextualization

Inventor: Curtis Christman (Spokane Valley, WA)
Assignee: Itron, Inc.
G06F16/248
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Quick Facts
Patent No.
US 12,248,489
App. No.
18/537,610
Granted
Mar 11, 2025
Kind
B2
Abstract

Techniques for contextualizing utility visualization patterns in a utility infrastructure environment are described herein. A utility meter data dashboard associated with a type of event may be displayed. A selection of a portion of a first utility visualization displayed in the utility meter data dashboard is received, the portion being associated with a subset of utility data. One or more previously used utility visualizations may be determined from among a plurality of additional utility visualizations. One or more candidate utility visualizations associated with the type of event may be determined from among the previously used utility visualizations. A ranked list of one or more candidate utility visualizations may be displayed. A second utility visualization may be displayed based at least in part on a selection from the ranked list.

Claims (61)

1. A method comprising:

receiving a selection of a portion of a first utility visualization, the portion being associated with a subset of utility data;

determining, based at least in part on the selection, a plurality of additional utility visualizations associated with the subset of the utility data;

determining, from among the plurality of additional utility visualizations, one or more previously used utility visualizations;

determining, from among the one or more previously used utility visualizations, one or more candidate utility visualizations that are associated with a type of utility event, wherein the candidate utility visualizations are determined by:

filtering the utility data to locate one or more data elements including one or more measurements, exceptions, or events, relevant with respect to identification of the type of utility event,

comparing the one or more data elements, by a pattern module, to one or more known patterns of measurements, known exceptions, or known events that are associated with the type of utility event;

determining a problem of interest associated with the type of utility event; and

determining, from among the one or more previously used utility visualizations, the one or more candidate utility visualizations that are associated with the problem of interest;

receiving a selection of at least a second utility visualization, from among a ranked list of the one or more candidate utility visualizations; and

outputting information associated with the second utility visualization.

2. The method of claim 1 , wherein the type of utility event comprises one or more of a fraud event, a fault event, or a false positive meter event.

3. The method of claim 1 , wherein the one or more previously used utility visualizations were used by one or more users to view the subset of the utility data or other utility data having a characteristic in common with the subset of the utility data.

4. The method of claim 1 , further comprising:

causing presentation of one or more user comments describing context for previous use of the one or more candidate utility visualizations.

5. The method of claim 1 , further comprising:

ranking the one or more candidate utility visualizations that are associated with the type of utility event.

6. The method of claim 5 , wherein the ranking is based at least in part on user feedback rating the one or more candidate utility visualizations.

7. The method of claim 1 , further comprising:

displaying the ranked list of the one or more candidate utility visualizations.

8. A system, comprising:

one or more processors; and

one or more non-transitory computer-readable media storing computer-executable instructions that, when executed on the one or more processors, cause the one or more processors to perform actions comprising:

receiving a selection of a portion of a first utility visualization, the portion being associated with a subset of utility data;

determining, based at least in part on the selection, a plurality of additional utility visualizations associated with the subset of the utility data;

determining, from among the plurality of additional utility visualizations, one or more previously used utility visualizations;

determining, from among the one or more previously used utility visualizations, one or more candidate utility visualizations that are associated with a type of utility event, wherein the candidate utility visualizations are determined by:

filtering the utility data to locate one or more data elements including one or more measurements, exceptions, or events, relevant with respect to identification of the type of utility event,

comparing the one or more data elements, by a pattern module, to one or more known patterns of measurements, known exceptions, or known events that are associated with the type of utility event;

determining a problem of interest associated with the type of utility event; and

determining, from among the one or more previously used utility visualizations, the one or more candidate utility visualizations that are associated with the problem of interest;

receiving a selection of at least a second utility visualization, from among a ranked list of the one or more candidate utility visualizations; and

outputting information associated with the second utility visualization.

9. The system of claim 8 , the actions further comprising:

causing presentation of one or more user comments describing context for previous use of the one or more candidate utility visualizations.

10. The system of claim 8 , wherein the one or more previously used utility visualizations were used by one or more users to view the subset of the utility data or other utility data having a characteristic in common with the subset of the utility data.

11. The system of claim 8 , wherein the first utility visualization is associated with the type of utility event, the type of utility event comprising one or more of a fraud event, a fault event, or a false positive meter event.

12. The system of claim 8 , the actions further comprising:

ranking the one or more candidate utility visualizations that are associated with the type of utility event.

13. The system of claim 8 , the actions further comprising:

displaying the ranked list of the one or more candidate utility visualizations.

14. A method comprising:

receiving a selection of a portion of a first utility visualization of a type of chart representing utility data, the portion being associated with a subset of the utility data;

determining, based at least in part on the selection, a plurality of additional utility visualizations associated with the subset of the utility data;

determining, from among the plurality of additional utility visualizations, one or more previously used utility visualizations;

determining, from among the one or more previously used utility visualizations, one or more candidate utility visualizations that are associated with a type of utility event, wherein the candidate utility visualizations are determined by:

filtering the utility data to locate one or more data elements including one or more measurements, exceptions, or events, relevant with respect to identification of the type of utility event,

comparing the one or more data elements, by a pattern module, to one or more known patterns of measurements, known exceptions, or known events that are associated with the type of utility event;

determining a problem of interest associated with the type of utility event; and

determining, from among the one or more previously used utility visualizations, the one or more candidate utility visualizations that are associated with the problem of interest;

receiving a selection of at least a second utility visualization, from among a ranked list of the one or more candidate utility visualizations; and

displaying, based at least in part on the selection, the second utility visualization.

15. The method of claim 14 , wherein the type of utility event comprises one or more of a fraud event, a fault event, or a false positive meter event.

16. The method of claim 14 , wherein the one or more previously used utility visualizations were used by one or more users to view the subset of the utility data or other utility data having a characteristic in common with the subset of the utility data.

17. The method of claim 14 , further comprising:

causing presentation of one or more user comments describing context for previous use of the one or more candidate utility visualizations.

18. The method of claim 14 , further comprising:

ranking the one or more candidate utility visualizations that are associated with the type of utility event.

19. The method of claim 18 , wherein the ranking is based at least in part on user feedback rating the one or more candidate utility visualizations.

20. The method of claim 14 , further comprising:

displaying the ranked list of the one or more candidate utility visualizations.

Assignments (2)
SECURITY INTEREST Recorded Sep 15, 2025
From: ITRON, INC.
To: WELLS FARGO BANK, NATIONAL ASSOCIATION
Reel/Frame 072870/0873 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 12, 2023
From: CHRISTMAN, CURTIS
To: ITRON, INC.
Reel/Frame 065849/0754 →
Continuity (2)
Continuation 17948617 · Sep 20, 2022
Related Publication 20240134872A1 · Apr 25, 2024
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