Assessment of Metaverse wearable technologies for smart livestock farming through a neuro quantum spherical fuzzy decision-making model

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dc.authorid0000-0002-8072-031X
dc.authorid0000-0002-9858-1266
dc.contributor.authorEcer, Fatih
dc.contributor.authorYaran Ögel, İlkin
dc.contributor.authorDinçer, Hasan
dc.contributor.authorYüksel, Serhat
dc.date.accessioned2024-07-18T05:39:45Z
dc.date.available2024-07-18T05:39:45Z
dc.date.issued2024
dc.departmentİstanbul Medipol Üniversitesi, İşletme ve Yönetim Bilimleri Fakültesi, Uluslararası Ticaret ve Finansman Bölümü
dc.description.abstractLivestock wearable technologies are innovations designed to ensure livestock health management. However, the user aspect of these devices from farmers’ perspective is still questionable. Additionally, livestock wearables are still in progress compared to the other wearables. Thus, this research aims to identify key design features regarding wearable smart collars (WSCs) and rank the alternative WSC prototypes within Metaverse, allowing farmers to select the best wearable device. To this end, an integrated neuro quantum spherical fuzzy multi-criteria decision-making (MCDM) framework is introduced via facial expressions to obtain the priority weights of WSC criteria with the improved decision-making trial and evaluation laboratory (DEMATEL) approach and to rank the WSC alternatives in Metaverse through the improved multi-objective optimization based on ratio analysis (MOORA) model. The novelties of this research are: (1) to build and introduce a novel decision support tool based on facial expressions, expert recommendations, and the quantum spherical fuzzy sets, (2) to guide industrial designers about the essential features of WSCs, whereas they are designing these devices, and (3) to help smallholder farmers to decide on the best WSC to enhance animal welfare and efficiency of animal production. Concerning the findings, “sound and stress analyzer” is the most significant feature, followed by “disease detection” and “price.” Moreover, Prototype 3 is the best WSC for farmers to adopt for livestock health management. Some essential implications are further presented.
dc.identifier.citationEcer, F., Yaran Ögel, İ., Dinçer, H. ve Yüksel, S. (2024). Assessment of Metaverse wearable technologies for smart livestock farming through a neuro quantum spherical fuzzy decision-making model. Expert Systems with Applications, 255. http://dx.doi.org/10.1016/j.eswa.2024.124722
dc.identifier.doi10.1016/j.eswa.2024.124722
dc.identifier.issn0957-4174
dc.identifier.issn1873-6793
dc.identifier.scopus2-s2.0-85198024418
dc.identifier.scopusqualityQ1
dc.identifier.urihttp://dx.doi.org/10.1016/j.eswa.2024.124722
dc.identifier.urihttps://hdl.handle.net/20.500.12511/12724
dc.identifier.volume255
dc.identifier.wos001267290000001en_US
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorDinçer, Hasan
dc.institutionauthorYüksel, Serhat
dc.language.isoen
dc.relation.ispartofExpert Systems with Applicationsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectFacial Expressions
dc.subjectLivestock Health Management
dc.subjectMetaverse
dc.subjectNeuro Quantum Decision-Making
dc.subjectSmart Livestock Farming
dc.subjectWearable Technology
dc.titleAssessment of Metaverse wearable technologies for smart livestock farming through a neuro quantum spherical fuzzy decision-making model
dc.typeArticle

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