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Virtual Disaggregation

Discover how much your appliances consume energy without installing any hardware.

Virtual Disaggregation

What we care about

NILM Powered disaggregation

Non Intrusive Load Monitoring identifies the major sub-consumptions in your buildings

No hardware required

Our machine learning models use existing hardware and DEXMA’s database of historical consumption

High accuracy

More than 95% accuracy in load disaggregation for tertiary buildings

Gauge the key loads in each of your buildings

Virtual disaggregation techniques allow you to pinpoint the main energy expenditures in your portfolio and compare the results of your buildings.

Enhance your virtual energy audits and enrich other services like recommendation engines or demand response measures.

Virtual doesn’t mean inaccurate

Our large database (more than 60,000 locations with many years of historical readings), portfolios’ metadata and existing hardware train and test our load disaggregation machine learning algorithms with an accuracy greater than 95%.

Save tons of money in hardware

The non-intrusive approach spares you time and installation costs so you can start saving right now. Initiate your portfolio audits without visiting or installing hardware.

Stop waiting 6 months to take relevant decisions

Start from day 1 to make key decisions in your energy efficiency project. Delays due to hardware installation are a thing of the past.

Every activity, its own disaggregation

A restaurant consumes differently than a hotel or an office building. NILM algorithms are trained with relevant data so they disaggregate relevant consumptions for each activity.


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