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November 21, 2022 | 10:00 – November 23, 2022 | 17:00 UTC+1
European Big Data Value Forum / EBDVF 2022 under the headline: “At the Heart of the Ecosystem for Data & AI” takes place in Prague, Czech Republic.
Program with the involvement of RICAIP and its partner – CIIRC CTU:
Monday, 21 November 2022
Wednesday, 23 November 2022
Guided tours in the RICAIP Testbed for Industry 4.0. at CIIRC CTU
The visit to the RICAIP Testbed for Industry 4.0 will introduce you a set of machines and algorithms that enable to build experimental flexible production lines and their parts, to develop, implement and verify novel solutions for Industry 4.0 needs. There are two options for a one-hour visit (21st and 23rd of November). The first tour will be guided by the director of the Testbed for Industry 4.0, Dr. Pavel Burget, the second tour by Tomáš Jochman, junior researcher.
Tuesday, 22 November 2022
The automotive industry is at the center of gravity of many different and connected economy streams from, for example, steel, chemicals, and textiles to ICT, repair, and mobility services. Moreover, It Is facing substantial transformation changes connected with the implementation of the EU Green Deal.Large volumes of data produced during the manufacturing process as well as data collected during vehicles lifetime, represent an immense source of information for all the stakeholders involved in the ecosystem.
This session will bring on stage knowledgeable representatives from the automotive industry and research that will elaborate on their most promising results on data management and data processing to face the challenges of the manufacturing in the near future. Their ideas leverage and extend the Industry 4.0 principles with the focus on automotive industry needs.
The role of BDVA, IDSA, Catena-X on one side and CLAIRE and ELLIS on the other will be documented.
The current trends in the second decade of the Industry 4.0 initiative will be highlighted and discussed, namely the massive deployment of AI and needs in well-structured and standardized data spaces. AI is used to achieve the new goals (e.g., energy efficiency, explainable AI for human-robot collaboration and integration, zero-error production). Data spaces should support the standardized digital platforms and represent efficient Machine Learning sources for the AI goals mentioned above.