BIG DATA FOR INDUSTRY 4.0: A CONCEPTUAL FRAMEWORK

被引：0

作者：

Gokalp, Mert Onuralp ^{[1
]}

Kayabay, Kerem ^{[1
]}

Akyol, Mehmet Ali ^{[1
]}

Eren, P. Erhan ^{[1
]}

Kocyigit, Altan ^{[1
]}

机构：

[1] Middle East Tech Univ, Inst Informat, Ankara, Turkey

来源：

2016 INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE & COMPUTATIONAL INTELLIGENCE (CSCI) | 2016年

关键词：

Industry; 4.0; big data; data flow based programming languages; machine learning; data mining;

D O I：

10.1109/CSCI.2016.87

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Exponential growth in data volume originating from Internet of Things sources and information services drives the industry to develop new models and distributed tools to handle big data. In order to achieve strategic advantages, effective use of these tools and integrating results to their business processes are critical for enterprises. While there is an abundance of tools available in the market, they are underutilized by organizations due to their complexities. Deployment and usage of big data analysis tools require technical expertise which most of the organizations don't yet possess. Recently, the trend in the IT industry is towards developing prebuilt libraries and dataflow based programming models to abstract users from low-level complexities of these tools. After briefly analyzing trends in the literature and industry, this paper presents a conceptual framework which offers a higher level of abstraction to increase adoption of big data techniques as part of Industry 4.0 vision in future enterprises.

引用

页码：431 / 434

页数：4

共 13 条

[1]

Altintas I, 2004, P INT C SCI STAT DAT, V16, P423, DOI DOI 10.1109/SSDM.2004.1311241

[2]

Berthold MR., 2009, ACM SIGKDD Explor. Newsl., V11, P26, DOI [DOI 10.1145/1656274.1656280, DOI 10.1145/1656274]

[3]

Bifet A, 2010, J MACH LEARN RES, V11, P1601

[4]

Blackstock M., 2012, P 3 INT WORKSH WEB T, P1

[5]

Chen H., 2012, Business Intelligence and Analytics: From Big Data to Big Impact Quarterly-Business Intelligence and Analytics: From Big Data to Big Impact, V36

[6]

Demsar J, 2004, LECT NOTES ARTIF INT, V3202, P537

[7] A Cloud Based Architecture for Distributed Real Time Processing of Continuous Queries [J].

Gokalp, Mert Onuralp ;

Kocyigit, Altan ;

Eren, P. Erhan .

PROCEEDINGS 41ST EUROMICRO CONFERENCE ON SOFTWARE ENGINEERING AND ADVANCED APPLICATIONS SEAA 2015, 2015, :459-462

[8]

Kayabay K., 2016, 3 INT MAN INF SYST C, P298

[9] Service innovation and smart analytics for Industry 4.0 and big data environment [J].

Lee, Jay ;

Kao, Hung-An ;

Yang, Shanhu .

PRODUCT SERVICES SYSTEMS AND VALUE CREATION: PROCEEDINGS OF THE 6TH CIRP CONFERENCE ON INDUSTRIAL PRODUCT-SERVICE SYSTEMS, 2014, 16 :3-8

[10]

Mayer S, 2014, INT CONF PERVAS COMP, P163, DOI 10.1109/PerComW.2014.6815188

← 1 2 →