{"title":"A Match Made in Semantics: Physics-infused Digital Twins for Smart Building Automation","authors":"Ganesh Ramanathan, Simon Mayer","doi":"arxiv-2406.13247","DOIUrl":null,"url":null,"abstract":"Buildings contain electro-mechanical systems that ensure the occupants'\ncomfort, health, and safety. The functioning of these systems is automated\nthrough control programs, which are often available as reusable artifacts in a\nsoftware library. However, matching these reusable control programs to the\ninstalled technical systems requires manual effort and adds engineering cost.\nIn this article, we show that such matching can be accomplished fully\nautomatically through logical rules and based on the creation of semantic\nrelationships between descriptions of \\emph{physical processes} and\ndescriptions of technical systems and control programs. For this purpose, we\npropose a high-level bridging ontology that enables the desired rule-based\nmatching and equips digital twins of the technical systems with the required\nknowledge about the underlying physical processes in a self-contained manner.\nWe evaluated our approach in a real-life building automation project with a\ntotal of 34 deployed air handling units. Our data show that rules based on our\nbridging ontology enabled the system to infer the suitable choice of control\nprograms automatically in more than 90\\% of the cases while avoiding almost an\nhour of manual work for each such match.","PeriodicalId":501310,"journal":{"name":"arXiv - CS - Other Computer Science","volume":"50 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Other Computer Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2406.13247","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Buildings contain electro-mechanical systems that ensure the occupants'
comfort, health, and safety. The functioning of these systems is automated
through control programs, which are often available as reusable artifacts in a
software library. However, matching these reusable control programs to the
installed technical systems requires manual effort and adds engineering cost.
In this article, we show that such matching can be accomplished fully
automatically through logical rules and based on the creation of semantic
relationships between descriptions of \emph{physical processes} and
descriptions of technical systems and control programs. For this purpose, we
propose a high-level bridging ontology that enables the desired rule-based
matching and equips digital twins of the technical systems with the required
knowledge about the underlying physical processes in a self-contained manner.
We evaluated our approach in a real-life building automation project with a
total of 34 deployed air handling units. Our data show that rules based on our
bridging ontology enabled the system to infer the suitable choice of control
programs automatically in more than 90\% of the cases while avoiding almost an
hour of manual work for each such match.