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Cited 8 time in webofscience Cited 10 time in scopus
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Energy-Efficient Forest Fire Prediction Model Based on Two-Stage Adaptive Duty-Cycled Hybrid X-MAC Protocol

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dc.contributor.authorKang, Jin-Gu-
dc.contributor.authorLim, Dong-Woo-
dc.contributor.authorJung, Jin-Woo-
dc.date.accessioned2023-04-28T07:41:48Z-
dc.date.available2023-04-28T07:41:48Z-
dc.date.issued2018-09-
dc.identifier.issn1424-8220-
dc.identifier.issn1424-3210-
dc.identifier.urihttps://scholarworks.dongguk.edu/handle/sw.dongguk/9151-
dc.description.abstractThis paper proposes an adaptive duty-cycled hybrid X-MAC (ADX-MAC) protocol for energy-efficient forest fire prediction. The Asynchronous sensor network protocol, X-MAC protocol, acquires additional environmental status details from each forest fire monitoring sensor for a given period, and then changes the duty-cycle sleep interval to efficiently calculate forest fire occurrence risk according to the environment. Performance was verified experimentally, and the proposed ADX-MAC protocol improved throughput by 19% and was 24% more energy efficient compared to the X-MAC protocol. The duty-cycle was shortened as forest fire probability increased, ensuring forest fires were detected at faster cycle rate.-
dc.language영어-
dc.language.isoENG-
dc.publisherMDPI-
dc.titleEnergy-Efficient Forest Fire Prediction Model Based on Two-Stage Adaptive Duty-Cycled Hybrid X-MAC Protocol-
dc.typeArticle-
dc.publisher.location스위스-
dc.identifier.doi10.3390/s18092960-
dc.identifier.scopusid2-s2.0-85053082385-
dc.identifier.wosid000446940600219-
dc.identifier.bibliographicCitationSENSORS, v.18, no.9-
dc.citation.titleSENSORS-
dc.citation.volume18-
dc.citation.number9-
dc.type.docTypeArticle-
dc.description.isOpenAccessY-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaChemistry-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalResearchAreaInstruments & Instrumentation-
dc.relation.journalWebOfScienceCategoryChemistry, Analytical-
dc.relation.journalWebOfScienceCategoryEngineering, Electrical & Electronic-
dc.relation.journalWebOfScienceCategoryInstruments & Instrumentation-
dc.subject.keywordAuthorforest fire-
dc.subject.keywordAuthorprediction model-
dc.subject.keywordAuthorenergy efficient-
dc.subject.keywordAuthorsensors-
dc.subject.keywordAuthorWireless Sensor Network-
dc.subject.keywordAuthorX-MAC-
dc.subject.keywordAuthorhybrid-
dc.subject.keywordAuthoradaptive-
dc.subject.keywordAuthorduty-cycle-
dc.subject.keywordAuthorprotocol-
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