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Semantic Cloud System for Scaling Data Science Solutions for Welding at Bosch

Abstract

Background and Challenges. Industry 4.0 focuses on smart factories that rely on IoT tech- nology for automation. This produces massive amounts of production data, increasing the demand for data-driven solutions and cloud technology. Yet, users of these solutions and cloud technology are often not cloud experts, such as domain experts and data scientists (Fig. 1.1). In a standard setting of a data science project, the team requires extensive assistance from cloud experts, whenever they want to deploy solutions or make small changes to their solutions deployed on the cloud. To facilitate the adoption of cloud systems careful planing to balance cost and benefits is required. Scaling data science solutions presents challenges of handling high data volume and enabling a broader users which are non-cloud experts to use cloud systems.
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Category

Academic article

Language

English

Author(s)

  • Zhuoxun Zheng
  • Baifan Zhou
  • Zhipeng Tan
  • Ognjen Savkovic
  • Diego Rincon-Yanez
  • Nikolay Nikolov
  • Titi Roman
  • Ahmet Soylu
  • Evgeny Kharlamov

Affiliation

  • SINTEF Digital / Sustainable Communication Technologies
  • Free University of Bozen-Bolzano
  • RWTH Aachen University
  • Bosch Center for Artificial Intelligence
  • University of Oslo
  • OsloMet - Oslo Metropolitan University
  • University of Santander

Year

2023

Published in

CEUR Workshop Proceedings

Volume

3632

View this publication at Norwegian Research Information Repository