Energy sub-metering and IoT: how to better control your consumption
Energy sub-metering and IoT allow you to control your consumption in order to reduce your costs and improve energy performance….
BERGER-LEVRAULT
BERGER-LEVRAULT
Berger-Levrault is an international software publisher based in France, serving local authorities and administrations, healthcare establishments, and the world of education and industry.
Berger-Levrault works with its clients and partners to make the world simpler and safer, thanks to a secure digital environment accessible to all.
Committed to responsible digital transformation, Berger-Levrault’s 2,000 employees work daily to meet the social, economic, and environmental challenges of their clients by creating trusted digital solutions.
Buildings involved in the project: 3 office buildings: Labège (31), Limonest (69), Villeneuve-sur-Lot (47)
In the current context of the transition to a more energy-efficient and environmentally friendly economy, the issue of energy management in buildings is becoming crucial. Berger-Levrault shares its experience of the deployment of its BL.Predict AI/IoT platform in its premises, highlighting the challenges encountered, the solutions deployed and the results obtained.
At the heart of its internal Corporate Social Responsibility (CSR) policy, Berger-Levrault has set itself a threefold objective: to control electricity consumption, reduce energy bills, and improve employee comfort. Faced with these challenges, the need to implement effective and sustainable solutions is a priority.
To meet these challenges, Berger-Levrault has deployed its BL.Predict AI/IoT platform in three of its buildings in Labège, Limonest, and Villeneuve-sur-Lot. This initiative aims to collect and analyse a multitude of data relating to energy consumption and occupant comfort conditions.
IoT sensors have been installed on the premises to monitor parameters such as temperature, humidity, carbon dioxide, and energy consumption, among others. This data is collected in real-time, providing an accurate and comprehensive picture of energy performance and comfort in buildings.
The benefits of this deployment are significant and demonstrate the effectiveness of the solution:
In addition, identifying malfunctions and improving employee comfort are tangible benefits of this approach.
On the strength of the convincing results obtained, Berger-Levrault is planning to extend the deployment of BL.Predict to other Group sites, to continue to optimise infrastructures and better adapt employees’ working conditions, particularly in a flex-office context.
In conclusion, the success of this project demonstrates Berger-Levrault’s commitment to responsible and sustainable energy management. It also demonstrates the relevance of AI/IoT solutions in transforming buildings into real players in the energy transition.
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