Rajagopal K Iyengar

US Patent:

20210018334, Jan 21, 2021

Filed:

Jul 19, 2019

Appl. No.:

16/516615

Inventors:

- Redwood Shores CA, US
Woei Ling LEOW - San Francisco CA, US
Rajagopal IYENGAR - San Francisco CA, US

International Classification:

G01D 4/00
G06K 9/62
G01D 4/02
G06Q 10/06
G06N 20/00
G06F 17/11

Abstract:

Embodiments predict an occurrence of one or more hot sockets among a meter installation of a plurality of smart meters. Embodiments receive historical data over a predefined time period from the plurality of smart meters, the historical data including, for each smart meter, an amount of daily consumption of electricity for the meter, historical meter events for the meter, and all service orders associated with the meter. Embodiments pre-process the historical data to generate hot socket features. Embodiments train a machine algorithm using the hot socket features, and use the trained machine algorithm to predict the occurrence of one or more hot sockets.

US Patent:

20200122598, Apr 23, 2020

Filed:

May 23, 2019

Appl. No.:

16/420597

Inventors:

- Redwood Shores CA, US
Woei Ling LEOW - San Francisco CA, US
Rajagopal IYENGAR - Oakland CA, US

International Classification:

B60L 53/66
G06N 20/00
G06N 5/04
H04W 4/021

Abstract:

Systems, methods, and other embodiments associated with detecting an electric vehicle charging event. In one embodiment, from electricity consumption data from a known set of electric vehicle owners, the method encodes usage values from time intervals with a symbol from a series of symbols representing a level of electricity consumption during the time interval. The encoding generates an encoded consumption pattern of symbols for each electrical vehicle owner. An EV charge motif is identified that represents an EV charging event. One or more machine learning classifiers is trained to identify the EV charge motifs from the known set of electric vehicle owners and to distinguish from non-charge motifs to identify EV charges from unknown data sets.