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dc.contributor.authorKalibatienė, Diana
dc.contributor.authorMiliauskaitė, Jolanta
dc.contributor.authorDzemydienė, Dalė
dc.contributor.authorMaskeliūnas, Saulius
dc.date.accessioned2023-09-18T16:11:47Z
dc.date.available2023-09-18T16:11:47Z
dc.date.issued2021
dc.identifier.issn0868-4952
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/112268
dc.description.abstractNowadays, there is a lack of smart marine monitoring systems, which have possibilities to integrate multi-dimensional components for monitoring and predicting marine water quality and making decisions for their optimal operations with minimal human intervention. This research aims to extend the smart coastal marine monitoring by proposing a solar energy planning and control component. The proposed approach involves the adaptive neuro-fuzzy inference system (ANFIS) for the wireless buoys, working online during the whole year in the Baltic Sea near the Lithuanian coast. The usage of our proposed fuzzy solar energy planning and control components allows us to prolong the lifespan of batteries in buoys, so it has a positive impact on sustainable development. The novelty and advantage of the proposed approach lie in establishing the ANFIS-based model to predict and control solar energy in a buoy for different lighting and temperature conditions depending on the four year seasons and to make a decision to transfer the collected data. The energy planning and consumption system for the wireless sensor network of buoys is carefully evaluated, and its prototype is developed. The proposed approach can be practically used for environmental monitoring, providing stakeholders with relevant and timely information for sound decision-making about hydro-meteorological situations in coastal marine water.eng
dc.formatPDF
dc.format.extentp. 795-816
dc.format.mediumtekstas / txt
dc.language.isoeng
dc.relation.isreferencedbyScience Citation Index Expanded (Web of Science)
dc.relation.isreferencedbySocial Sciences Citation Index (Web of Science)
dc.relation.isreferencedbyScopus
dc.relation.isreferencedbyCurrent Contents
dc.relation.isreferencedbyINSPEC
dc.rightsLaisvai prieinamas internete
dc.source.urihttps://informatica.vu.lt/journal/INFORMATICA/article/1239/text
dc.source.urihttps://talpykla.elaba.lt/elaba-fedora/objects/elaba:114787766/datastreams/MAIN/content
dc.titleDevelopment of a fuzzy inference based solar energy controller for smart marine water monitoring
dc.typeStraipsnis Web of Science DB / Article in Web of Science DB
dcterms.licenseCreative Commons – Attribution – 4.0 International
dcterms.references63
dc.type.pubtypeS1 - Straipsnis Web of Science DB / Web of Science DB article
dc.contributor.institutionVilniaus Gedimino technikos universitetas
dc.contributor.institutionVilniaus universitetas
dc.contributor.facultyFundamentinių mokslų fakultetas / Faculty of Fundamental Sciences
dc.subject.researchfieldN 009 - Informatika / Computer science
dc.subject.researchfieldT 007 - Informatikos inžinerija / Informatics engineering
dc.subject.studydirectionB01 - Informatika / Informatics
dc.subject.studydirectionF04 - Jūrų technologijos / Maritime technology
dc.subject.enmarine water monitoring
dc.subject.enbuoys
dc.subject.enadaptive neural fuzzy inference system (ANFIS)
dc.subject.enfuzzy controller
dc.subject.enwireless sensor network (WSN)
dc.subject.enPhotovoltaic (PV) system
dc.subject.enenergy optimization
dcterms.sourcetitleInformatica
dc.description.issueiss. 4
dc.description.volumevol. 32
dc.publisher.nameVilniaus universiteto leidykla
dc.publisher.cityVilnius
dc.identifier.doi000735200800006
dc.identifier.doi10.15388/21-INFOR470
dc.identifier.elaba114787766


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