VEIC Author
Nick Lange
Dan Fredman
Partners & Clients
Sense Labs

If Automated Metering Infrastructure (AMI) data-driven savings today is what we can see above the water, then what’s the 90% of energy savings iceberg hidden below? New answers are suggested by recent findings from approaches that bring device-level disaggregation, and smartphone ecosystem integration towards a more perfect union of technologies and a focus on the people they serve.

We assess next generation home energy monitoring systems—those that are using machine learning and intensive computation—in their effort to make the kernel of truth in the one-liner for home energy monitoring: “mean time to kitchen drawer” a thing of the past. We’ll share a framework for energy stakeholders (utilities, policy-makers, etc.) to better understand and consider how this enabling suite of capabilities (high sampling rates, real-time low-latency feedback, and a consumer-friendly orientations) may affect their approach to accelerating market transformation through future research, pilot programs, services, and regulations.

The paper’s perspective is anchored by a review of first-hand experiences and novel findings and results from a selection of case studies. It will include qualitative customer insights and large-scale energy analyses based on thousands of devices in the field. Although even the most aggressive forecasts indicate that we are likely a decade or two away from when most things in most homes are smart and connected, this review of the latest behind-the-meter products and services may help us start to better conceptualize the energy systems of the future that are driven by a new kind of EM&V: Engagement, Meaning, and Value.

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