★ GREEN BUTTON ENERGY ANALYTICS ★        Recognized by the U.S. CTO & Dept. of Energy        ★ Early Machine Learning · Consumer Energy Tech · 2011–2012 ★            

Green Button Energy Analytics

2011 – 2012  ·  Systems Integration & Early ML  ·  Austin, TX

[ SCREENSHOT: Energy usage dashboard or data visualization ]

★ Recognized by the United States Chief Technology Officer and the Department of Energy for innovation in consumer-facing energy technology. ★


Background

In 2011, the Obama administration and the Department of Energy launched the Green Button initiative — a commitment from major utilities to give electricity customers access to their own energy usage data in a standardized, machine-readable format.

It was a significant moment. For the first time, there was a common standard for home energy data that developers could actually build on. Most people in the industry were focused on smart meters and grid infrastructure. I saw it differently: what if you took that raw data and built something consumers could actually use?

[ SCREENSHOT: Green Button data standard or app prototype ]

What I Built

I built one of the first analytics applications on top of the Green Button standard — before most people in the tech industry had heard of it.

  • Ingested and parsed Green Button XML energy data from utility providers
  • Applied early machine learning models for usage pattern analysis
  • Anomaly detection to flag unusual consumption events
  • Consumer-facing dashboard surfacing actionable insights
  • Recommendations engine for reducing energy waste based on detected patterns

The ML work was early-stage — this was 2011, years before the modern deep learning era — but the signal was clear: even simple models on high-quality time-series energy data could surface genuinely useful insights for consumers.

[ PHOTO: DOE recognition event or demo screenshot ]

Recognition

The project was recognized by the United States CTO and the Department of Energy as a standout example of innovative use of the Green Button standard in consumer energy technology.

It was a meaningful signal — and an early lesson in something I've come back to many times since: when a new data standard, protocol, or API gets released, there's usually a six-to-twelve month window where the people who build on top of it first have a real advantage. The same logic has applied to every new IoT protocol, AI API, and government dataset I've worked with since.

Connection to Yonomi

This project planted the seed for my interest in connected device infrastructure. The challenge of turning raw, standardized data into a useful consumer experience — and doing it before the market catches up — became a recurring theme in my career. Yonomi was, in many ways, the same idea at a much larger scale.

Read about Yonomi

Machine LearningEnergy AnalyticsGreen Button Data VisualizationConsumer TechDOE Recognition U.S. CTOObama Administration

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