A context-aware method-based cattle vocal classification for livestock monitoring in smart farm

dc.contributor.authorSattar, Farook
dc.date.accessioned2022-10-27T19:43:32Z
dc.date.available2022-10-27T19:43:32Z
dc.date.copyright2022en_US
dc.date.issued2022
dc.description.abstractThis paper focuses on livestock monitoring on a smart farm to improve animal well-being and production. The great potential for increased automation and technological innovation in agriculture could help livestock farmers to monitor the welfare of their animals for precision livestock farming. A new acoustical method exploiting contextual information is introduced for cattle vocal classification. The proposed scheme considers the raw recordings which contain cattle sounds. Then a set of contextual acoustic features is constructed as input to the MSVM classifier to track the types of cattle vocalizations. Categorized noisy cattle calls are finally classified into four types of calls (i.e., cattle food anticipating call, animal estrus call, cough sound, and normal call) with an overall classification accuracy of 84% outperforming the results obtained using conventional MFCC features. We used an open access dataset consists of 270 cattle classification records acquired using multiple sound sensors. Promising results are obtained by the proposed method for livestock monitoring enabling farm owners to determine the status of their cattle.en_US
dc.description.reviewstatusRevieweden_US
dc.description.scholarlevelFacultyen_US
dc.identifier.citationFarook Sattar (2022). “A context-aware method-based cattle vocal classification for livestock monitoring in smart farm.” Chemistry Proceedings, 10(1), 89. https://doi.org/10.3390/IOCAG2022-12233en_US
dc.identifier.urihttps://doi.org/10.3390/IOCAG2022-12233
dc.identifier.urihttp://hdl.handle.net/1828/14344
dc.language.isoenen_US
dc.publisherChemistry Proceedingsen_US
dc.subjectsmart farm
dc.subjectcattle vocalization
dc.subjectclassification
dc.subjectlivestock monitoring
dc.subjectprecision livestock farming
dc.subject.departmentDepartment of Electrical and Computer Engineering
dc.titleA context-aware method-based cattle vocal classification for livestock monitoring in smart farmen_US
dc.typeArticleen_US

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