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Smart data and the industrial internet of things

 
: Beecks, C.; Rasheed, H.; Grass, A.; Devasya, S.; Jentsch, M.; Soto, J.A.C.; Tavakolizadeh, F.; Linnemann, A.; Eisenhauer, M.

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Volltext (PDF; )

Vermesan, O.:
Next Generation Internet of Things : Distributed Intelligence at the Edge and Human Machine-to-Machine Cooperation
Aalborg: River Publishers, 2018 (River Publishers Series in Communications)
ISBN: 978-87-7022-008-8
ISBN: 978-87-7022-007-1
S.175-206
Englisch
Aufsatz in Buch, Elektronische Publikation
Fraunhofer FIT ()

Abstract
Many modern production processes are nowadays equipped with cyber-physical systems in order to capture, manage, and process large amounts of sensor data including information about machines, processes, and products. The proliferation of cyber-physical systems (CPS) and the advancement of Internet of Things (IoT) technologies have led to an explosive digitization of the industrial sector. Driven by the high-tech strategy of the federal government in Germany, many manufacturers across all industry segments are accelerating the adoption of cyber-physical system and IoT technologies to gain actionable insight into their industrial production processes and finally improve their processes by means of data-driven methodology. In this work, we aim to give insights into our recent research regarding the domains of Smart Data and Industrial Internet of Things (IIoT). To this end, we are focusing on the EU projects MONSOON and COMPOSITION as examples for the Public-Private Partnership (PPP) initiatives Factories of the Future (FoF) and Sustainable Process Industry (SPIRE) and show how to approach data analytics via scalable and agile analytic platforms. Along these analytic platforms, we provide an overview of our recent Smart Data activities and exemplify data-driven analysis of industrial production processes from the process and manufacturing industries.

: http://publica.fraunhofer.de/dokumente/N-581327.html