Use AI to Increase the efficiency of wind turbines and solar parks and to increase the accuracy of forecasting.
Enable EU stakeholders to offer better renewable energy production facilities, with reduced maintenance costs, and accurate return of investment prediction.
Create a data analytics platform that will be able to manage extreme loads of sensor streaming data and time series.
Provide accurate forecasting and prediction through AI algorithms that work over huge volumes of streaming data.
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.
MORE receives funding from the European Union's Horizon 2020 Research and Innovation programme under Grant Agreement No. 957345.
