dEsign enVironmEnt foR Extreme-Scale big data analyTics
on heterogeneous platforms


In the last decade we have witnessed a significant increase in information flows exchanged, with data from various sources and qualities.

Data collection is extremely widespread: their selection, interpretation and validation has a critical impact on society, the environment and industry.
The technological challenge is to extract high-value knowledge from this huge and diverse information stream.
To meet this specific need, it is necessary to develop innovative analysis methods, characterized by high standards of performance and efficiency, with an approach based on artificial intelligence.

The EVEREST project (October 2020 – September 2023), funded by the European Commission under the Horizon 2020 program and coordinated by IBM Research GmbH and Politecnico di Milano, involves also Duferco Energia among its industrial partners.

The main target is the creation of a hardware and software infrastructure dedicated to the analysis and processing of “big data”, which increases computing efficiency and simplifies the development of heterogeneous and distributed architecture programs.
The design approach, based on the objectivity of numbers (“data driven”), uses artificial intelligence and hardware acceleration.

EVEREST will validate its method in application cases of great relevance and interest in the environmental, social and business fields.
Duferco Energia will participate in the development of an application based on advanced meteorological models for the forecast of renewable energy to be sold on short-term markets.

The application will support the forecasting of the production, use and marketing of renewable wind, solar and hydroelectric energy, reducing the risks associated with major rising / falling events in market prices.
The application will make use of high-resolution weather forecasts on an hourly basis, real-time data acquisition and artificial intelligence models.

The other scenarios of the EVEREST project include:

An application for monitoring air quality in industrial sites, combined with weather forecasts to predict the effects of chemical agents on the environment and allow proactive planning of production and the activation of treatments to reduce emissions.

An application for road traffic high resolution modeling in real time, to reduce congestion and improve travel safety.