Projektbeschreibung
Vorteile der sektorübergreifenden Datenintegration
Im heutigen digitalen Zeitalter stellen die Integration und Analyse umfangreicher Datenströme eine große Herausforderung dar, insbesondere im Bereich der cyber-physischen Produkte mit hohem Volumen. Gleichzeitig nimmt die Bedeutung der nahtlosen Integration und Analyse verschiedener Datenströme immer weiter zu. In diesem Zusammenhang ist das Ziel des EU-finanzierten Projekts Cross-CPP, eine innovative IT-Umgebung zu schaffen, um diese Herausforderungen zu bewältigen. Das Team nutzt offene Datenquellen aus, um neue sektorübergreifende Dienste einzurichten und gleichzeitig durch einen kontextsensitiven Ansatz das Geschäftsgeheimnis, Datenschutz, geistige Eigentumsrechte und ethische Erwägungen zu berücksichtigen. Die Forschenden werden neue Modelle aufstellen, ein Marktplatz-Ökosystem schaffen und Instrumente zur Echtzeitanalytik bereitstellen. Die praktischen Anwendungsmöglichkeiten der Projektergebnisse sind vielfältig. Insgesamt soll über das Projekt eine Zukunft der vernetzten Industrien gefördert werden.
Ziel
The objective is to establish an IT environment for the integration and analytics of data streams coming from high volume (mass) products with cyber physical features, as well from Open Data Sources, aiming to offer new cross sectorial services and focusing on the commercial confidentiality, privacy and IPR and ethical issues using an context sensitive approach. The project addresses cross-stream analysis of large data volumes from mass cyber physical products (CPP) from various industrial sectors such as automotive, and home automation. The business objective of the research is to allow for analyses of such data streams in combination to other (non-industrial, open) data streams and for the establishment of diverse enhanced sectorial and cross-sectorial services. The project will develop: (i) New models for integration and analytics of data streams coming from multi-sectorial CPP, including shared systems of entity identifiers applicable to multi-sectorial CPP (as well as the definition of agreed data models for data streams from multiple CPP aiming at defacto standard; (ii) Ecosystem, including a common Marketplace, and methodology to use such models to build multi-sectorial cloud based services, (iii) Toolbox for real-time and predictive cross-stream analytics, context modelling and extraction, and dynamically changing security policy, privacy and IPR conditions/rules and (iv) set of services such as services based on a combination of data streams from home automation and (electrical) vehicles to provide enhanced local weather forecast and predict and optimise energy consumptions in households. The project will build upon the results from past and current projects, where results from the project AutoMat, addressing services developed based on data streams from vehicles, will be used as a basis for further development aiming to extend it to integrated, cross-sectorial data streams analytics.
Wissenschaftliches Gebiet
- natural sciencesearth and related environmental sciencesatmospheric sciencesmeteorology
- natural sciencescomputer and information sciencesdata sciencebig data
- social sciencessociologyindustrial relationsautomation
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensors
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringcontrol systemshome automation
Programm/Programme
Thema/Themen
Aufforderung zur Vorschlagseinreichung
Andere Projekte für diesen Aufruf anzeigenUnterauftrag
H2020-ICT-2017-1
Finanzierungsplan
IA - Innovation actionKoordinator
28359 Bremen
Deutschland