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    Implementation of a Large-Scale Platform for Cyber-Physical System Real-Time Monitoring

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    URI: http://hdl.handle.net/11556/726
    ISSN: 2169-3536
    DOI: 10.1109/access.2019.2911979
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    Author/s
    Canizo, Mikel; Conde, Angel; Charramendieta, Santiago; Minon, Raul; Cid-Fuentes, Raul G.; [et al.]
    Date
    2019
    Keywords
    Anomaly detection
    Big data
    Cyber-physical system
    Industry 4.0
    Real-time processing
    Abstract
    The emergence of Industry 4.0 and the Internet of Things (IoT) has meant that the manufacturing industry has evolved from embedded systems to cyber-physical systems (CPSs). This transformation has provided manufacturers with the ability to measure the performance of industrial equipment by means of data gathered from on-board sensors. This allows the status of industrial systems to be monitored and can detect anomalies. However, the increased amount of measured data has prompted many companies to investigate innovative ways to manage these volumes of data. In recent years, cloud computing and big data technologies have emerged among the scientific communities as key enabling technologies to address the current needs of CPSs. This paper presents a large-scale platform for CPS real-time monitoring based on big data technologies, which aims to perform real-time analysis that targets the monitoring of industrial machines in a real work environment. This paper is validated by implementing the ...
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