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Process-aware IIoT Knowledge Graph: A semantic model for Industrial IoT integration and analytics.

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Title: Process-aware IIoT Knowledge Graph: A semantic model for Industrial IoT integration and analytics.
Authors: Diamantini, Claudia1 (AUTHOR) c.diamantini@univpm.it, Mircoli, Alex1 (AUTHOR) a.mircoli@univpm.it, Potena, Domenico1 (AUTHOR) d.potena@univpm.it, Storti, Emanuele1 (AUTHOR) e.storti@univpm.it
Source: Future Generation Computer Systems. Feb2023, Vol. 139, p224-238. 15p.
Subjects: Knowledge graphs, Ontologies (Information retrieval), Internet of things, Set functions, Industry 4.0, Data extraction
Abstract: The integration of the huge data streams produced by the Industrial Internet of Things (IIoT) can provide invaluable knowledge in the context of Industry 4.0, and is also an open research issue. The present paper proposes a semantic approach to this issue, centred around the notion of process as the backbone. We build an ontology describing the fundamental elements involved in IIoT and their relations, and discuss the construction of the Process-aware IIoT Knowledge Graph, where raw sensor data are enriched with information about process activities and the physical production environment. We also propose a framework for querying the Knowledge Graph, and we demonstrate its capabilities by considering the production of metal accessories as case study. • A semantic approach for integration of Industrial Internet of Things data streams • An ontology to build a Process-aware IioT Knowledge Graph • A set of functions enabling data extraction and graph manipulations [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
Description
Abstract:The integration of the huge data streams produced by the Industrial Internet of Things (IIoT) can provide invaluable knowledge in the context of Industry 4.0, and is also an open research issue. The present paper proposes a semantic approach to this issue, centred around the notion of process as the backbone. We build an ontology describing the fundamental elements involved in IIoT and their relations, and discuss the construction of the Process-aware IIoT Knowledge Graph, where raw sensor data are enriched with information about process activities and the physical production environment. We also propose a framework for querying the Knowledge Graph, and we demonstrate its capabilities by considering the production of metal accessories as case study. • A semantic approach for integration of Industrial Internet of Things data streams • An ontology to build a Process-aware IioT Knowledge Graph • A set of functions enabling data extraction and graph manipulations [ABSTRACT FROM AUTHOR]
ISSN:0167739X
DOI:10.1016/j.future.2022.10.003