MORE | Management of Real-time Energy Data - Goals


Green Energy | MORE - Management of Real-time Energy Data
MORE | Management of Real-time Energy Data - Green Energy

Use AI to Increase the efficiency of wind turbines and solar parks and to increase the accuracy of forecasting.

Industrial Leadership | MORE - Management of Real-time Energy Data
MORE | Management of Real-time Energy Data - Industrial Leadership

Enable EU stakeholders to offer better renewable energy production facilities, with reduced maintenance costs, and accurate return of investment prediction.

Extreme data analytics | MORE - Management of Real-time Energy Data
MORE | Management of Real-time Energy Data - Extreme data analytics

Create a data analytics platform that will be able to manage extreme loads of sensor streaming data and time series.

Accurate forecasting | MORE - Management of Real-time Energy Data
MORE | Management of Real-time Energy Data - Accurate forecasting

Provide accurate forecasting and prediction through AI algorithms that work over huge volumes of streaming data.

MORE | Management of Real-time Energy Data - In a nutshell


MORE will deliver a platform that will address the technical challenges in time series and stream management, focusing on the RES industry. More specifically, MORE’s platform will introduce an architecture that combines edge computing and cloud computing to be able to address both responsiveness and the need for sophisticated analytics simultaneously. This architecture will be combined with the usage of time series summarization techniques, or as we more accurately term them in MORE, modelling techniques for sensor data. Models are any compressed representations that allow the reconstruction of the original data points of a time series (e.g. a linear function) within a known error-bound (possibly zero). This approach has synergies with the edge computing approach, since summarization can be done at the edge, reducing the load in the whole data processing pipeline. The key objective of MORE is the following:



MORE will allow stakeholders in industry sectors with huge volumes of sensor data, especially the RES industry, to: a) scale the management of streaming and historical time series beyond an order of magnitude beyond the state-of-art and b) to perform forecasting, prediction and diagnostics using the whole data that is available to them with accuracy that outperforms existing approaches.

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Thessaloniki International Fair 2021 | MORE - Management of Real-time Energy Data

MORE | Management of Real-time Energy Data - THESSALONIKI INTERNATIONAL FAIR 2021

MORE participates in the 85th Thessaloniki International Fair, which will take place with a physical presence at the Thessaloniki International Exhibition Center. This year's event is dedicated to Greece, with the central theme of the triptych Past-Present-Future, in the context of the 200th anniversary of the Greek Revolution. The aim is to contribute to the redefinition of the needs of Greek society, to stimulate its historical memory and to bring closer the citizen with the new digital services and technologies, the innovations, but also the Greek production. We are waiting for you at the stand of the General Secretariat for Research and Innovation (HALL 7, STAND 3) from 11 to 19 September.

MORE General Logo | MORE - Management of Real-time Energy Data

MORE | Management of Real-time Energy Data - Plenary Meeting

The seventh general meeting was held on 22/07/2021 virtually due to the pandemic of COVID-19. However, MORE continues and technology gave as an alternative channel to stay connected and updated.

MORE General Logo | MORE - Management of Real-time Energy Data

MORE | Management of Real-time Energy Data - Plenary Meeting

The sixth general meeting was held on 17/06/2021 virtually due to the pandemic of COVID-19. However, MORE continues and technology gave as an alternative channel to stay connected and updated.

MORE General Logo | MORE - Management of Real-time Energy Data

MORE | Management of Real-time Energy Data - Deliverable:" D2.3 Edge Data Ingestion Module - Initial Version"

The aim of this deliverable is to document how ModelarDB has been modified to efficiently ingest sensor data when running on edge nodes. The existingversion of ModelarDB is optimized for the data centernodes as it interfaces with unmodified versions of Apache Spark and Apache Cassandra for query processing and storage respectively. Thus, the emphasis is on selecting and integrating an alternative open-source query engine and storage layer that are optimized for the edge nodes. The storage layer is required to store the ingested data until it can be transferred to the data centernodes, while the query engine is required to execute queries on the sensor data during ingestion.

MORE | Management of Real-time Energy Data - Partners


Athena Innovation Center | MORE - Management of Real-time Energy Data
AAU | MORE - Management of Real-time Energy Data
Inaccess | MORE - Management of Real-time Energy Data
IBM | MORE - Management of Real-time Energy Data
Perception Dynamics | MORE - Management of Real-time Energy Data
ENGIE Laborelec | MORE - Management of Real-time Energy Data
Modelar Data | MORE - Management of Real-time Energy Data

MORE | Management of Real-time Energy Data - Contact