Big Data

AKKA, Via Its Big Data Platform, Joins Forces With SYLFEN

AKKA Group

BIG DATA AND AUTONOMOUS BUILDING

The AKKA Group (Paris:AKA) (BSE:AKA) (ISIN:FR0004180537), European leader in engineering consultancy and R&D services in the mobility sector and Data Science expert is joining forces with the Grenoble-based start-up SYLFEN via its Big Data platform in order to develop the building of the future, self-sufficient in renewable energy.

SYLFEN develops integrated solutions that help building owners to make a successful energy transition. In order to minimise the environmental impact of buildings, responsible for 36% of greenhouse gas emissions in Europe, SYLFEN is working on the transition to a decentralised, decarbonised and digitalised energy.

SYLFEN has developed the Smart Energy Hub, a modular equipment that can be integrated into any building thanks to an innovative hydrogen technology hybridised with batteries.

This system allows – in addition to other renewable energy sources – not only to store surplus renewable electricity by charging batteries and producing green hydrogen, but also to supply the building with electricity and heat from locally produced stored energy (batteries, hydrogen) or natural gas (cogeneration).

AKKA, partner and Big Data expert

SYLFEN’s objective is to provide its clients with (i) an automatic, predictive and optimised energy flow control for each building, (ii) a communication on environmental and energy performance and (iii) a service of predictive maintenance. To meet this objective, AKKA teams have operated in processing the large volume of data generated by integrating the Big Data platform into SYLFEN’s information system.

AKKA’s Big Data platform is an integrated platform that manages the entire data processing chain. It allows to massively collect heterogeneous data from SYLFEN (solar production, electrical and thermal consumption of buildings, technical data, etc.) and to facilitate data visualisation and mining.

First use cases have already been implemented and SYLFEN teams are trained for an independent long-term usage of the Big Data platform, enabling them to control, develop and improve algorithms for energy efficiency as well as for production and consumption forecasting.

AKKA’s contribution to this project highlights the Group’s Big Data expertise and illustrates its ambition to reduce the ecological footprint of existing infrastructures and vehicles through technology and innovation.

Denis Grandjean, Akka’s Business Unit Director, says: “We are delighted to be associated with a promising French start-up which brings an innovation wave in this evolving sector. We relied on our Data Centre of Expertise to carry out the project. The availability of our Big Data platform and the expertise of AKKA & SYLFEN teams will enable us to speed up data enhancement and, ultimately, time-to-market of SYLFEN’s equipment. Value-added services for customers can thus be quickly developed, bringing an additional competitive advantage to SYLFEN. »

Nicolas Bardi, President of SYLFEN, adds: “In all our hardware and software developments, we seek to focus our efforts on innovations that have the greatest impact on our customers, by relying on the best partners to save time and to integrate industrial solutions. Our partnership with AKKA, which provides us with its expertise and strong reactivity, is an essential asset for SYLFEN’s commercial success. »

NOTE FOR EDITORS:

What is the AKKA Big Data platform?

AKKA’s Big Data Platform is an integrated platform, available immediately. It manages the entire data processing chain and allows to massively collect heterogeneous data. It provides great flexibility in data visualisation and exploration, in restitution, in addition to natively integrating machine learning tools. It can therefore be used to present first concrete results very quickly. Entirely based on open-source components, the AKKA big data platform includes several functions such as:

  • high-volume data collection and storage (including archiving);
  • data analysis;
  • data transformation (ETL function);
  • development of predictive models;
  • development of real-time and batch applications;
  • data exposure via web services and databases;
  • data visualisation using interactive dashboards;
  • deployment of applications within the platform itself or to other types of environments.

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