%0 Conference Proceedings
%T Streaming Analytics in Edge-Cloud Environment for Logistics Processes
%+ University of Bremen
%+ National Technical University of Athens [Athens] (NTUA)
%+ University of Piraeus
%A Stietencron, Moritz, Von
%A Lewandowski, Marco
%A Lepenioti, Katerina
%A Bousdekis, Alexandros
%A Hribernik, Karl
%A Apostolou, Dimitris
%A Mentzas, Gregoris
%Z Part 4: Data-Driven Applications in Smart Manufacturing and Logistics Systems
%< avec comité de lecture
%( IFIP Advances in Information and Communication Technology
%B IFIP International Conference on Advances in Production Management Systems (APMS)
%C Novi Sad, Serbia
%Y Bojan Lalic
%Y Vidosav Majstorovic
%Y Ugljesa Marjanovic
%Y Gregor von Cieminski
%Y David Romero
%I Springer International Publishing
%3 Advances in Production Management Systems. Towards Smart and Digital Manufacturing
%V AICT-592
%N Part II
%P 245-253
%8 2020-08-30
%D 2020
%R 10.1007/978-3-030-57997-5_29
%K Data analytics
%K Machine learning
%K Predictive maintenance
%K Aviation
%Z Computer Science [cs]Conference papers
%X The recent advancements in Internet of Things (IoT) technology and the increasing amount of sensing devices that collect and/or generate massive sensor data streams enhances the use of streaming analytics for providing timely and meaningful insights. The current paper proposes a framework for supporting streaming analytics in edge-cloud computational environment for logistics operations in order to maximize the potential value of IoT technology. The proposed framework is demonstrated in a real-life scenario of a large transportation asset in the aviation sector.
%G English
%Z TC 5
%Z WG 5.7
%2 https://inria.hal.science/hal-03635614/document
%2 https://inria.hal.science/hal-03635614/file/504014_1_En_29_Chapter.pdf
%L hal-03635614
%U https://inria.hal.science/hal-03635614
%~ IFIP
%~ IFIP-AICT
%~ IFIP-TC
%~ IFIP-TC5
%~ IFIP-WG
%~ IFIP-APMS
%~ IFIP-WG5-7
%~ IFIP-AICT-592