Univers
Energy

Total Energies

 

An innovative tool

Determined to become the world leader in the renewable energy sector, TotalÉnergies called on SFEIR to help its cross-functional R&D team. Our team helped industrialize the Machine Learning process.

 

 

Overview

TotalÉnergies wants to speed up the installation of solar panels on private homes. Thanks to its new Solar Mapper tool, TotalÉnergies is able to quickly provide an accurate estimate of the solar energy potential of the home.

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Challenge

  • Deployment of several use cases around the analysis of satellite images
  • Creating pipelines in usable Earth Engine models
  • Creation of a web platform to help show and demonstrate the new use cases developed by the R&D teams

Solution

In partnership with Google, SFEIR has participated in the development and industrialization of machine learning models based on satellite images.

The team implemented the model training and deployment pipelines. A web application has been developed to democratize the use of these models throughout the TotalÉnergies organization.

    Framework

    TensorFlow

    Plateforme

    Google Earth Engine, Google Cloud Platform

    Portal

    ReactJS, NodeJS

Everything worked very well in this partnership between SFEIR, Google and TotalÉnergies. If we had to start over, I would do exactly the same.

Gilles Poulain, R&D Project Manager, TotalÉnergies

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