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Towards Interoperability Mismatch Identification. An Expert System Approach
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.ORCID iD: 0000-0002-1736-5589
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.ORCID iD: 0000-0002-9412-6872
2022 (English)In: IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society, IEEE, 2022Conference paper, Published paper (Refereed)
Abstract [en]

Lack of interoperability is a growing problem for the industry and the adoption of new technologies. Despite the current efforts in digitization and automatization, challenges regarding the integration and compatibility between heterogeneous devices and systems remain open. In the literature, new solutions can be found. To adopt them, the identification of the differences between service interfaces that hamper communication is critical. Automating the analysis and identification, which is currently based on manual operations, would significantly reduce the engineering effort and associated costs.This paper proposes a novelty approach to autonomously select the most suitable solution to address interoperability problems in the communication between heterogeneous systems. This work introduces the mismatch analysis system, designed as an expert system through the use of production rules, frames and fuzzy logic. The mismatch analysis system calculates the degree of compatibility and uncertainty between service interfaces and decides the best course of action to assist the communication between systems. The system has been successfully designed, implemented, integrated, and tested in the Arrowhead framework, demonstrating high potential.

Place, publisher, year, edition, pages
IEEE, 2022.
Series
Annual Conference of Industrial Electronics Society, ISSN 1553-572X, E-ISSN 2577-1647
Keywords [en]
Arrowhead framework, Degree of Compatibility, Expert System, Interoperability
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Cyber-Physical Systems
Identifiers
URN: urn:nbn:se:ltu:diva-95048DOI: 10.1109/IECON49645.2022.9968897Scopus ID: 2-s2.0-85143899053ISBN: 978-1-6654-8025-3 (electronic)OAI: oai:DiVA.org:ltu-95048DiVA, id: diva2:1722488
Conference
IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society, Brussels, Belgium, October 17-20, 2022
Funder
European Commission, EU ECSEL, 826452Available from: 2022-12-29 Created: 2022-12-29 Last updated: 2025-01-08Bibliographically approved

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Paniagua, Cristina

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