Some benefits of BL.Predict for you… and for us!

Berger Levrault Building.

Because we are all concerned by the Energy Sobriety Plan and the Decarbonization Strategy, it seemed natural to us to extend the deployment of our AI/IoT platform BL.Predict to… our own premises!

As part of the Berger-Levrault Group’s internal CSR policy, our objective is twofold:

  • To optimize the energy consumption of our buildings;
  • To improve the comfort of our employees.

A project revealing our daily practices

From November 2022, we have equipped 3 buildings:

  • Two with the largest surface area: in Labège (31) and in Limonest (69)
  • The third in Villeneuve-sur-Lot (47), where the datacenter is located.

In total, there are 24 sensors spread throughout the open spaces, for more than 20,000 consumption data collected daily.

Visible results from the first few months

The first results are visible after less than 4 months of monitoring and data analysis. The implementation of corrective actions and the raising of awareness of daily eco-actions have led to a 7% decrease in total electricity consumption, i.e. 4.2 tons of CO2 avoided. With BL.Predict, the internal rate of return is estimated at €8,350 in just one and a half months, for a monthly rate estimated at €6,000 per month.

In detail…

Locally, at the Labège building, savings of 24% over 4 months were achieved by adapting the heating settings according to the outside temperature for a better distribution of heat, particularly in the entrance hall and certain specific rooms.

At the Limonest building, electricity consumption was reduced by 5% over two months, thanks in particular to repairs to the free cooling system, the installation of programmable sockets and an adjustment of temperature settings. Measurements to verify CO2 levels and temperatures now show a satisfactory level of comfort.

Finally, at the Villeneuve-sur-Lot building, a malfunction in the heating system is causing significant heat disparities, which is currently being repaired.

In addition to actively participating in the energy challenge, the deployment of BL.Predict in our premises further emphasizes the benefits of a frugal digital approach to achieve real and short-term ecological impacts.

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