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A cloud-to-edge architecture for predictive analytics

: Bowden, David; Marguglio, Angelo; Morabito, Lucrezia; Napione, Chiara; Panicucci, Simone; Nikolakis, Nikolaos; Makris, Sotiris; Coppo, Guido; Andolina, Salvatore; Macii, Alberto; Macii, Enrico; O'Mahony, Niamh; Becker, Paul; Jung, Sven

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Papotti, P.:
Workshops of the EDBT/ICDT 2019 Joint Conference. Proceedings. Online resource : Lisbon, Portugal, March 26, 2019
Lisbon, 2019 (CEUR Workshop Proceedings 2322)
7 S.
International Conference on Extending Database Technology (EDBT) <2019, Lisbon>
International Conference on Database Theory (ICDT) <2019, Lisbon>
Workshop "Data Analytics Solutions for Real-Life Applications" (DARLI-AP) <2019, Lisbon>
European Commission EC
H2020; 767561; SERENA
VerSatilE plug-and-play platform enabling remote pREdictive mainteNAnce
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IPT ()
predictive maintenance; edge computing; cloud architecture; smart data acquisition

Data management and processing to enable predictive analytics in cyber physical systems, holds the promise of creating insight into the underlying processes, discovering criticalities and predicting imminent problems. Hence, proactive strategies can be adopted, with respect to predictive analytics. This paper discusses the design and prototype implementation of a plug-n-play end-to-end cloud architecture, enabling predictive maintenance of industrial equipment. This is enabled by integrating edge gateways, data stores at both the edge and the cloud, and various applications, such as predictive analytics, visualization and scheduling, integrated as services in the cloud system. The proposed approach has been implemented into a prototype and tested in an industrial use case related to the maintenance of a robotic arm.