P. Skobelev, V. Larukhin, E. Simonova, O. Goryanin, V. Yalovenko, O. Yalovenko
{"title":"Multi-agent approach for developing a digital twin of wheat","authors":"P. Skobelev, V. Larukhin, E. Simonova, O. Goryanin, V. Yalovenko, O. Yalovenko","doi":"10.1109/SMARTCOMP50058.2020.00062","DOIUrl":null,"url":null,"abstract":"The paper is devoted to development of a digital twin (DT) of plant. It is built as a smart system based on the knowledge base on macrostages of plant development and multiagent technology that allows for detailed monitoring and control of plant development, recalculation of forecast, namely, assessment of vegetation quality, future yield and timing for onset of next stages. It uses transition rules between stages upon receipt of data from agronomists on the state of plant development, as well as the actual and forecast weather data. The paper proposes a conceptual plant model based on ontologies and multi-agent technology, which is a network of linked states and transition rules that correspond to macrostages of plant development with the possibility of recalculating their parameters. The paper also covers the main principles of agronomist work with the digital twin of plant.","PeriodicalId":346827,"journal":{"name":"2020 IEEE International Conference on Smart Computing (SMARTCOMP)","volume":"259 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE International Conference on Smart Computing (SMARTCOMP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SMARTCOMP50058.2020.00062","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
The paper is devoted to development of a digital twin (DT) of plant. It is built as a smart system based on the knowledge base on macrostages of plant development and multiagent technology that allows for detailed monitoring and control of plant development, recalculation of forecast, namely, assessment of vegetation quality, future yield and timing for onset of next stages. It uses transition rules between stages upon receipt of data from agronomists on the state of plant development, as well as the actual and forecast weather data. The paper proposes a conceptual plant model based on ontologies and multi-agent technology, which is a network of linked states and transition rules that correspond to macrostages of plant development with the possibility of recalculating their parameters. The paper also covers the main principles of agronomist work with the digital twin of plant.