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시불변/시변 환경에서의 센서 노드 배치 계획

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dc.contributor.author이수용-
dc.date.accessioned2021-11-17T05:41:04Z-
dc.date.available2021-11-17T05:41:04Z-
dc.date.created2021-11-15-
dc.date.issued2021-
dc.identifier.issn1976-5622-
dc.identifier.urihttps://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/18122-
dc.description.abstractSensor networks are widely used in various environments, especially that that are unreachable for humans, or where long-term monitoring is required. In most of the previously reported sensor network studies, the focus was on energy consumption based on sensing range and communication strength with a large number of sensor nodes deployed a priori. Herein, we describe a sensor node placement that uses a single mobile node or small number of nodes. Initially, a small number of nodes are used under an unknown environment and hence they sparsely distributed. Based on the estimated spatial gradient at each node, extra nodes are added. For a time-varying environment, another sensor placement algorithm based on the heat conductivity theory is introduced. The intermittent sensing schedule requires an efficient node placement such that the distribution of sensor nodes enables an impartial measurement. The quantitative measure, which represents the degree of variance with respect to time, was introduced while estimating the spatial gradient. Thus, using both the algorithms accordingly will enable time-efficient and energy-efficient measurements for unknown environments.-
dc.language한국어-
dc.language.isoko-
dc.publisher제어·로봇·시스템학회-
dc.title시불변/시변 환경에서의 센서 노드 배치 계획-
dc.title.alternativeSensor Nodes Placement in Time Invariant/Time Varying Environment-
dc.typeArticle-
dc.contributor.affiliatedAuthor이수용-
dc.identifier.doi10.5302/J.ICROS.2021.21.0125-
dc.identifier.scopusid2-s2.0-85120684054-
dc.identifier.bibliographicCitation제어.로봇.시스템학회 논문지, v.27, no.11, pp.851 - 857-
dc.relation.isPartOf제어.로봇.시스템학회 논문지-
dc.citation.title제어.로봇.시스템학회 논문지-
dc.citation.volume27-
dc.citation.number11-
dc.citation.startPage851-
dc.citation.endPage857-
dc.type.rimsART-
dc.identifier.kciidART002772901-
dc.description.journalClass1-
dc.description.journalRegisteredClassscopus-
dc.description.journalRegisteredClasskci-
dc.subject.keywordAuthorSensor node-
dc.subject.keywordAuthorspatial gradient-
dc.subject.keywordAuthorperturbation/correlation-
dc.subject.keywordAuthortime-varying environment-
dc.subject.keywordAuthor.-
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