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Digital Twins for A...
Digital Twins for Anomaly Detection in the Industrial Internet of Things : Conceptual Architecture and Proof-of-Concept
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- De Benedictis, A. (författare)
- Department of Electrical Engineering and Information Technology, University of Naples Federico II, Via Claudio, Naples, 21-80138, Italy
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- Flammini, Francesco, Senior Lecturer, 1978- (författare)
- Mälardalens universitet,Innovation och produktrealisering
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- Mazzocca, N. (författare)
- Department of Electrical Engineering and Information Technology, University of Naples Federico II, Via Claudio, Naples, 21-80138, Italy
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- Somma, A. (författare)
- Department of Electrical Engineering and Information Technology, University of Naples Federico II, Via Claudio, Naples, 21-80138, Italy
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- Vitale, F. (författare)
- Department of Electrical Engineering and Information Technology, University of Naples Federico II, Via Claudio, Naples, 21-80138, Italy
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(creator_code:org_t)
- IEEE Computer Society, 2023
- 2023
- Engelska.
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Ingår i: IEEE Transactions on Industrial Informatics. - : IEEE Computer Society. - 1551-3203 .- 1941-0050. ; 19:12, s. 11553-11563
- Relaterad länk:
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https://doi.org/10.1...
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- Modern cyber-physical systems based on the industrial Internet of Things (IIoT) can be highly distributed and heterogeneous, and that increases the risk of failures due to misbehavior of interconnected components, or other interaction anomalies. In this article, we introduce a conceptual architecture for IIoT anomaly detection based on the paradigms of digital twins (DT) and autonomic computing (AC), and we test it through a proof-of-concept of industrial relevance. The architecture is derived from the current state-of-the-art in DT research and leverages on the MAPE-K feedback loop of AC in order to monitor, analyze, plan, and execute appropriate reconfiguration or mitigation strategies based on the detected deviation from prescriptive behavior stored as shared knowledge. We demonstrate the approach and discuss results by using a reference operational scenario of adequate complexity and criticality within the European Railway Traffic Management System.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Datorsystem (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Computer Systems (hsv//eng)
Nyckelord
- Anomaly detection
- autonomic computing (AC)
- cyber-physical systems
- digital twins (DTs)
- industrial Internet of Things (IIoT)
- process mining (PM)
- Behavioral research
- Cyber Physical System
- Embedded systems
- Internet of things
- Railroad transportation
- Railroads
- Autonomic Computing
- Behavioral science
- Conceptual architecture
- Cybe-physical systems
- Industrial internet of thing
- Process mining
- Computer architecture
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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