Verdigris Technologies, Inc.

Jacques Kvam

Danny Serven

Michael Roberts

Daniela Li

Joe Phaneuf

Diego Torres

Anjali Sehrawat

Santo Ko

Jon Chu

Thomas Chung

Sami Shad

Jared Kruzek

Jason Goldman

Martin Chang

A current transformer having a body having an upper half and a lower half hingedly connected to the upper half, a pair of ferrite cores located within one of the upper half and the lower half of the body, the pair of ferrite cores defining a gap formed between each ferrite core of the pair of ferrite cores, and a sensor located within the gap formed between each ferrite core of the pair of ferrite cores.

Power monitoring and distributing systems

A method of managing energy by use of processing logic that comprises a load processor as a cloud service is provided. The method includes receiving power load information from a data collection system located at a building and using a cloud analysis layer that employs machine-learning and artificial intelligence for optimization control, analyzing the received power load information to disaggregate load waveform signals and identify device-based power loads by use of a neural network to perform historical device demand and performance analysis to generate device-based demand forecasting, generating demand forecasts for the building to mitigate peak demand based on analysis of a power draw signal and the generated device-based demand forecasting, and determining whether the generated demand forecast for the building is to peak in a near future, based on threshold values of at least one of generated device-based demand forecasting, power price or cost information, and user behavior analysis.

System and methods for power system forecasting using deep neural networks

A system and system for motor fault detection are provided. The system includes a data collection sensor electrically coupled to a motor, and a processor functioning as a Motor Current Signature analyzer (MCSA) detecting performance conditions of the motor based on a measured power draw current data captured by the sensor and providing condition information indicative of a fault in the motor based on the detected performance conditions. The method includes measuring, by a data collection sensor, power draw current data from the motor, detecting, by a processor functioning as a Motor Current Signature analyzer (MCSA), performance conditions of the motor based on the measured power draw current data, and providing condition information indicative of a fault in the motor based on the detected performance conditions to a user.

System and methods for fault detection

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Mountain View, CA, United States of America

Jacques Kvam