Energy

Advanced Sensor Analytics Platform

author Josh Miramant May 4, 2018

The Problem

PingThings was a startup looking to build a real-time platform to leverage machine-learning for physical systems on the electric utility grid and high-value industrial assets such as GSU transformers and step-down transformers. They wanted an analytics platform to track sensor data, focusing on storing and manipulating time-series data and modeling complex relationships between synchrophasors'​ high-resolution signals.

Sector Energy

Vertical Analytics

Model LightGBM/XGBoost

Case Study

Blue Orange helped build the first production prototype of PingThings’ PredictiveGrid. The PredictiveGrid is an Advanced Sensor Analytics Platform (ASAP) architected to ingest, store, access, visualize, analyze, and train machine learning and deep learning algorithms with sensor data measuring the grid with nanosecond temporal resolution.

Initial predictive problems addressed:

  • Rapid post-event analysis and reporting
  • Sensor data cleaning and management
  • Fault detection, prediction, and localization
  • Anomaly identification, classification, and prediction
  • Failure signature identification


Deep Learning Energy Machine Learning Predictive Analytics
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Full-service data transformation to make it easy to get from raw data to insights.


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