Invention Grant
- Patent Title: Systems and methods for utilizing machine learning to identify non-technical loss
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Application No.: US17816520Application Date: 2022-08-01
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Publication No.: US11886843B2Publication Date: 2024-01-30
- Inventor: Thomas M. Siebel , Edward Y. Abbo , Houman Behzadi , Avid Boustani , Nikhil Krishnan , Kuenley Chiu , Henrik Ohlsson , Louis Poirier , Jeremy Kolter
- Applicant: C3.AI, INC.
- Applicant Address: US CA Redwood City
- Assignee: C3.ai, Inc.
- Current Assignee: C3.ai, Inc.
- Current Assignee Address: US CA Redwood City
- Agency: Norton Rose Fulbright US LLP
- Main IPC: G06F8/34
- IPC: G06F8/34 ; G06N20/00 ; H04W52/04 ; H04B17/391 ; G06Q50/06 ; G01R21/00
Abstract:
Various embodiments of the present disclosure can include systems, methods, and non-transitory computer readable media configured to select a set of signals relating toa plurality of energy usage conditions. Signal values for the set of signals can be determined. Machine learning can be applied to the signal values to identify energy usage conditions associated with non-technical loss.
Public/Granted literature
- US20230027296A1 SYSTEMS AND METHODS FOR UTILIZING MACHINE LEARNING TO IDENTIFY NON-TECHNICAL LOSS Public/Granted day:2023-01-26
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