The widespread use of sensor and IoT devices is generating huge volumes of time series data in various industries like finance, energy, factories, medicine, manufacturing and others. Industries use these data for monitoring, but their main potential is still untapped. Existing techniques and software for time series management do not provide tools sufficiently scalable and sophisticated for managing the huge volumes of data or adequate forecasting, prediction and diagnostics. MORE will create a platform that will address the technical challenges in time series and stream management, focusing on the RES industry. MORE’s platform will introduce an architecture that combines edge computing and cloud computing to be able to guarantee both responsiveness and provide 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. MORE will introduce advanced analytics tools for prediction, forecasting and diagnostics based on two technological directions: machine learning and pattern extraction, with emphasis to motifs, which is the state-of-the-art for time series. MORE will adjust these techniques to work directly on models of data, thus enabling them to scale beyond state-of-the-art. The ability to ingest huge volumes of data will have an important impact to the accuracy of the prediction and diagnostics models.

The FIREFLY project rises to the sustainable evolution of the catalyst-based chemical industry, towards its electrification and reduced third-party dependence on metals and fossil energy. The controversial sustainability challenges and opportunities in catalysts recycling/production and catalyzed chemical processes motivated the synergy of 16 partners proposing the FIREFLY concept, relying on the development of: i) Electro-driven technologies for metal recycling from spent, waste, and off-specification catalysts available in Europeincluding a modelling, optimization, and engineering approach; ii) Efficient integration of renewable electricity; iii) A digital tool for predictive decision-making; iv) Production of (electro)catalysts for innovative (electro)chemical processes that overcome traditional production associated with high operating conditions, greenhouse gas emissions, and lack of circularity. The 48-month project foresees 3 stages: i) The technologies involved in the concept will be developed to TRL4, accompanied by an integrated sustainability assessment that will support the selection of the most promising technology routes based on their environmental and techno-economic performance. ii) The selected flowsheets will form the FIREFLY process, in a small-scale pilot. They will be demonstrated at TRL6 in the predictive, RES powered, and flexible production of new metal-based (electro)catalysts from secondary resources as well as in the application of these outputs in innovative (electro)chemical processes of selected chemicals: ammonia and hydrogen peroxide (with current environmental and operational concerns), depolymerization of lignin and biomass processing for bio-based chemicals (in support of defossilization of the chemical industry). iii) The activities and results will be effectively communicated, disseminated, and exploited to a wide set of stakeholders.

The scope of DYNAMO is to combine the two fields of business continuity management (BCM) and cyber threat intelligence (CTI) to generate a situational awareness picture for decision support across all stages of the resilience cycle (prepare, prevent, protect, response, recover). Professionals of different backgrounds will work together with end-users to develop, refine and combine selected tools into a single platform. In alignment to end-user needs, human factors, high ethical standards and societal impacts, DYNAMO includes the following goals: Resilience assessment as basis for BCM - An assessment with different levels of detail offers with varying existent data a fast or detailed evaluation of the investigated sector and helps to identify critical processes. - End-user data will be integrated to measure determined performance targets. With respect to the functional description, AI-based approaches will be used for a deeper understanding and potential self-learning of the interconnected process. - The results generate knowledge concerning susceptibility and vulnerability of the investigated sector. - The solutions support the BCM with respect to the five resilience phases. Leveraging CTI - CTI will be improved with respect to existing solutions (H2020 ECHO, PANACEA). - The H2020 Early Warning System (EWS) will be extended and integrated. A Malware Information Sharing Platform (MISP) will be used to raise the situational awareness between different security actors. - The CTI approach deliver data that will be integrated into the resilience and BCM approach. The use of AI will support the development. Solutions will be integrated with the Cyber Knowledge Graph to visualize the analysis of threat intelligence. The DYNAMO platform will be able to collect organization’s skills data, elaborate and create custom tailored organisational training to improve organisational resilience which will be demonstrated within three different (cross-)sectoral use-cases.