Streaming Analytics in Edge-Cloud Environment for Logistics Processes

被引：3
|
作者：
von Stietencron, Moritz [1 ]
Lewandowski, Marco [1 ]
Lepenioti, Katerina [2 ]
Bousdekis, Alexandros [2 ]
Hribernik, Karl [1 ]
Apostolou, Dimitris [2 ,3 ]
Mentzas, Gregoris [2 ]
机构：
[1] Univ Bremen, BIBA Bremer Inst Prod & Logist GmbH, Bremen, Germany
[2] Natl Tech Univ Athens NTUA, Inst Commun & Comp Syst ICCS, Informat Management Unit IMU, Athens, Greece
[3] Univ Piraeus, Dept Informat, Piraeus, Greece
来源：
ADVANCES IN PRODUCTION MANAGEMENT SYSTEMS: TOWARDS SMART AND DIGITAL MANUFACTURING, PT II | 2020年 / 592卷
基金：
欧盟地平线“2020”;
关键词：
Data analytics; Machine learning; Predictive maintenance; Aviation;
D O I：
10.1007/978-3-030-57997-5_29
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
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.
引用
收藏
页码：245 / 253
页数：9
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