Big-data-driven anomaly detection in industry (4.0): An approach and a case study

Proceedings - 2016 IEEE International Conference on Big Data, Big Data 2016

Volumn , Issue , 2016, Pages 1647-1652

  Stojanovic, Ljiljana ^a   Dinic, Marko ^b   Stojanovic, Nenad ^b   Stojadinovic, Aleksandar ^b  

^a FRAUNHOFER IOSB   (Germany)

^b Nissatech ^*  (Serbia)

Author keywords

Anomaly Detection; Big Data; CEP; Data driven Quality Control; Industrie 4.0

Indexed keywords

COMPUTER AIDED DESIGN; DATA HANDLING; INFORMATION MANAGEMENT; MICROWAVE OVENS; PROCESS CONTROL; QUALITY ASSURANCE; QUALITY CONTROL; QUALITY MANAGEMENT; SIGNAL DETECTION;

ANOMALOUS BEHAVIOR; ANOMALY DETECTION; DATA DRIVEN; DATA-DRIVEN ANOMALIES; INDUSTRIE 4.0; MULTI-DIMENSIONAL ANALYSIS; NON-LINEAR CORRELATIONS; REAL-TIME DETECTION;

BIG DATA;

EID: 85015218171     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/BigData.2016.7840777     Document Type: Conference Paper

References (4)

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3. http://static.googleusercontent.com/media/research.google.co m/en//archive/mapreduce-osdi04.pdf
4. Kang, Z., Yao, X., Kwok-Leung, T., System Informatics: From Methodology to Applications, IEEE Intelligent Systems, November/December 2015