No more uncertainties!

eensight is a next-generation machine learning tool that will contribute to the much-needed advancement of automated measurement and verification methods for energy efficiency. It will provide essential insights for investors, energy companies, legislators and building owners.

Advanced measurement and verification (M&V), sometimes called M&V 2.0, can lay the foundation for energy efficiency project aggregation schemes and/or energy efficiency support programs by providing the insights that are necessary for all parties involved in up-scaling energy efficiency to correctly evaluate risks and expected benefits. M&V 2.0 combines real-time data and predictive modeling methods so that to produce: (a) tools to understand the characteristics of a building’s energy consumption, and (b) continuous feedback on the most probable impact of an energy efficiency intervention.

As such, the eensight method can contribute significantly to the decarbonisation of the European building stock by increasing investments in energy efficiency retrofitting projects.

For a practical application, check out the e-book Rethinking Measurement and Verification of Energy Savings

The tool is reproducible and open-source, available for practitioners to experiment and test on different datasets.

To ease the work with the eensight tool, an instructional video is made available on the SENSEI YouTube channel.