{"title":"A semantic event based framework for complex situations modeling and identification in smart environments","authors":"Abderrahim Lakehal, A. Alti, P. Roose","doi":"10.19101/IJACR.PID33","DOIUrl":null,"url":null,"abstract":"Integration of technologies and smart services is an essential need in most pervasive smart automation systems, especially those requiring agile situation management such as a smart home. Ontology reasoning is an efficient technique for identifying the situation of such systems by capturing the context and optimizing connected object lifecycle. It is based on common-sense knowledge for interpreting a huge number of events from different and heterogeneous connected objects. The ontology-driven approach may be used to solve the parallel incoming events using new combination operators in order to achieve high accuracy rates. This paper presents a flexible, modular and hierarchical loosely coupled framework based on open semantic services in order to identify highly complex events to hold the situations with high efficiency. The proposed approach is evaluated on smart domains use cases and compared with other existing methods. Results show interesting ratios of situation identification accuracy with low execution time.","PeriodicalId":273530,"journal":{"name":"International Journal of Advanced Computer Research","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Advanced Computer Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.19101/IJACR.PID33","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
Integration of technologies and smart services is an essential need in most pervasive smart automation systems, especially those requiring agile situation management such as a smart home. Ontology reasoning is an efficient technique for identifying the situation of such systems by capturing the context and optimizing connected object lifecycle. It is based on common-sense knowledge for interpreting a huge number of events from different and heterogeneous connected objects. The ontology-driven approach may be used to solve the parallel incoming events using new combination operators in order to achieve high accuracy rates. This paper presents a flexible, modular and hierarchical loosely coupled framework based on open semantic services in order to identify highly complex events to hold the situations with high efficiency. The proposed approach is evaluated on smart domains use cases and compared with other existing methods. Results show interesting ratios of situation identification accuracy with low execution time.