Patent · US Active

Non-intrusive load monitoring using machine learning

US11593645B2 · kind B2 · utility

0Cited by

4References

18Claims

0Family size

Assignee

Oracle International Corporation · US

Inventors

Selim MIMAROGLU · Arlington, US
Oren BENJAMIN · Arlington, US
Arhan Gunel · Arlington, US
Anqi Shen · Arlington, US

Key dates

Filing date	Nov 27, 2019
Grant date	Feb 28, 2023
Priority date	—
Expiry date	Jul 30, 2041

Classification

Technology area (CPC Y)Emerging Cross-Sectional Technologies
CPC primaryY04S40/20
WIPO fieldComputer technology
WIPO sectorElectrical engineering

Abstract

Embodiments implement non-intrusive load monitoring using machine learning. A trained convolutional neural network (CNN) can be stored, where the CNN includes a plurality of layers, and the CNN is trained to predict disaggregated target device energy usage data from within source location energy usage data based on training data including labeled energy usage data from a plurality of source locations. Input data can be received including energy usage data at a source location over a period of time. Disaggregated target device energy usage can be predicted, using the trained CNN, based on the input data.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.