Abstract
Motivated by challenges that emerged from Complex Event Processing (CEP) in Big Data contexts, an Intelligent Event Broker (IEB) was previously proposed as a CEP system built on flexible and scalable Big Data technologies and techniques, being already applied to Industry 4.0 scenarios. A key feature of the IEB lies in an effective visualization system for meta-monitorization and management. An analysis of previous scientific and technical literature has shown scarcity of proposals or development of such mechanisms. This paper proposes a Web Visualization Platform for managing and monitoring an IEB system based on novel approaches that include interactive exploration techniques, tridimensional visualizations and mixed-reality environments. Being mainly targeted towards Industry 4.0, this paper presents a demonstration case at Bosch Car Multimedia Portugal. Results indicate that significant value can be obtained when the visualization system is applied to decision support scenarios within organizations foreseeing event processing, Big Data, and Industry 4.0 projects.
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Acknowledgements
This work has been supported by national funds through FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2019 and the Doctoral scholarship PD/BDE/135101/2017 and by European Structural and Investment Funds in the FEDER component, through the Operational Competitiveness and Internationalization Programme (COMPETE 2020) [Project nº 039479; Funding Reference: POCI-01-0247-FEDER-039479]. Authors acknowledge the Virtual and Augmented Reality work of Ana Dias, André Domingues, Maria Cardoso, Rui Faria and Vanessa Ferreira, the Bosch Car Multimedia and the 8thWall team that supported our work during the development phase.
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Rebelo, J., Andrade, C., Costa, C., Santos, M.Y. (2020). An Immersive Web Visualization Platform for a Big Data Context in Bosch’s Industry 4.0 Movement. In: Themistocleous, M., Papadaki, M. (eds) Information Systems. EMCIS 2019. Lecture Notes in Business Information Processing, vol 381. Springer, Cham. https://doi.org/10.1007/978-3-030-44322-1_6
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