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IASelect: finding best-fit agent practices in industrial CPS using graph databases
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Orientador(es)
Resumo(s)
The ongoing fourth Industrial Revolution depends mainly on robust Industrial Cyber-Physical Systems (ICPS). ICPS includes computing (software and hardware) abilities to control complex physical processes in distributed industrial environments.Industrialagents,originatingfromthewell-established multi-agent systems field, provide complex and cooperative control mechanisms at the software level, allowing us to develop larger and more feature-rich ICPS. The IEEE P2660.1 standardisation project, ”Recommended Practices on Industrial Agents: Integration of Software Agents and Low Level Automation Functions” focuses on identifying Industrial Agent practices that can benefit ICPS systems of the future. A key problem within this project is identifying the best-fit industrial agent practices for a given ICPS. This paper reports on the design and development of a tool to address this challenge. This tool, called IASelect, is built using graph databases and provides the ability to flexibly and visually query a growing repository of industrial agent practices relevant to ICPS. IASelect includes a front-end that allows industry practitioners to interactively identify best-fit practices without having to write manual queries.
Descrição
Palavras-chave
Cyber-physical systems Industrial agents Graph database Interfacing practices
Contexto Educativo
Citação
Sharma, Chandan; Sinha, Roopak ;Leitão, Paulo (2019). IASelect: finding best-fit agent practices in industrial CPS using graph databases. In 17th International Conference on Industrial Informatics (INDIN’19). Helsinki-Espoo; Finland. p.1558-1563