
INACCESS NETWORKS
INACCESS NETWORKS
4 Projects, page 1 of 1
assignment_turned_in Project2008 - 2010Partners:ITYE, University of Ulm, University of Essex, INACCESS NETWORKS, CNRSITYE,University of Ulm,University of Essex,INACCESS NETWORKS,CNRSFunder: European Commission Project Code: 216837All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=corda_______::a4b5c8f76ca61ae25ab95d8b2dc6c2ba&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eumore_vert All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=corda_______::a4b5c8f76ca61ae25ab95d8b2dc6c2ba&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euOpen Access Mandate for Publications and Research data assignment_turned_in Project2020 - 2023Partners:IBM (Ireland), MODELARDATA APS, AAU, LABORELEC, INACCESS NETWORKS +2 partnersIBM (Ireland),MODELARDATA APS,AAU,LABORELEC,INACCESS NETWORKS,ARC,PERCEPTION DYNAMICS LIMITEDFunder: European Commission Project Code: 957345Overall Budget: 3,720,550 EURFunder Contribution: 3,720,550 EURThe 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.
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For further information contact us at helpdesk@openaire.eumore_vert All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=corda__h2020::0e8e9ebd97bd86aa2d770736d5cb621e&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euassignment_turned_in Project2010 - 2013Partners:University of Catania, CRF, NXP (Germany), CSIC, LEITAT +14 partnersUniversity of Catania,CRF,NXP (Germany),CSIC,LEITAT,CSEM,INACCESS NETWORKS,University of Patras,STMicroelectronics (Switzerland),Unisa,POLITO,STU,MISSING_LEGAL_NAME,MIY,CONSORZIO NAZIONALE INTERUNIVERSITARIO PER LA NANO,Intracom Telecom (Greece),ON BELGIUM,ETH LAB,UNIBOFunder: European Commission Project Code: 120214All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=corda_______::7082a3837cce126371bf16ef76977646&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eumore_vert All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=corda_______::7082a3837cce126371bf16ef76977646&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euOpen Access Mandate for Publications and Research data assignment_turned_in Project2020 - 2024Partners:SOLAR COATING SOLUTIONS BV, SAIDEA, EPIA, TU Delft, EGP +18 partnersSOLAR COATING SOLUTIONS BV,SAIDEA,EPIA,TU Delft,EGP,RAPTECH SRL,3E,SOLAR CENTURY HOLDINGS LIMITED,teu,Huawei Technologies Duesseldorf GmbH,REUNIWATT SAS,DSM ADVANCED SOLAR B.V.,TUV RHEINLAND SOLAR GMBH,PVCASE,BAYWA R.E. OPERATION SERVICES SRL,EURAC,SOLAR MONKEY,ABOVE SURVEYING LTD,UCY,IMEC,ENDURANCE SOLAR SOLUTIONS BV,INACCESS NETWORKS,INNOSEAFunder: European Commission Project Code: 952957Overall Budget: 12,878,100 EURFunder Contribution: 9,969,040 EURTRUST-PV will demonstrate increase in performance and reliability of PV components (e.g. module O&M friendly design, inverter enabled O&M solutions, aftermarket coatings, extended testing beyond standard) and PV systems (e.g. more accurate yield models and assessment, data-driven mitigation measures from monitoring and advanced field inspection, reliability of novel system concepts such as floating PV) in large portfolios of distributed and/or utility scale PV. The TRUST-PV results will be tested and demonstrated from fab to field and all data gathered along the value chain will flow into a decision support system platform with enhanced decision-making using AI. The innovation at component level in TRUST-PV will be driven by the needs of stakeholders operating in a later stage of a PV project, i.e. Asset managers, EPC and O&M operators. TRUST-PV PV modules will thus become O&M friendly and inverter will enable rapid and cost-effective field inspection. The innovation at system level will fully exploit the digitalisation of the PV sector by linking 3D design with BIM concepts, developing more accurate models for yield assessments, and closing the gap between performance and failure detection through monitoring and field inspection. The innovation at the point of connection is based on the deployment of tailored strategies for the residential sector (better observability of performance with cost-effective monitoring solution, use of storage to enable renewable energy communities) and the utility sector (e.g. combination of advanced forecasting with storage and regulation through power plant controllers) with the final aim of improving the hosting capacity and increase stability. Finally, in TRUST-PV we envision a path of circular economy which enhances disposed components/material recovery for further use in the industry, to support progressive steps of plant repowering, aimed at increasing their production and lifetime without requiring additional land.
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For further information contact us at helpdesk@openaire.eu