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Dairy Cattle Rumen Bolus Developments with Special Regard to the Applicable Artificial Intelligence (AI) Methods.
Hajnal, Éva; Kovács, Levente; Vakulya, Gergely.
Afiliação
  • Hajnal É; Alba Regia Technical Faculty, Óbuda University, 1034 Budapest, Hungary.
  • Kovács L; Institute of Animal Sciences, Hungarian University of Agricultural and Life Sciences, 2100 Gödöllo, Hungary.
  • Vakulya G; Alba Regia Technical Faculty, Óbuda University, 1034 Budapest, Hungary.
Sensors (Basel) ; 22(18)2022 Sep 08.
Article em En | MEDLINE | ID: mdl-36146158
ABSTRACT
It is a well-known worldwide trend to increase the number of animals on dairy farms and to reduce human labor costs. At the same time, there is a growing need to ensure economical animal husbandry and animal welfare. One way to resolve the two conflicting demands is to continuously monitor the animals. In this article, rumen bolus sensor techniques are reviewed, as they can provide lifelong monitoring due to their implementation. The applied sensory modalities are reviewed also using data transmission and data-processing techniques. During the processing of the literature, we have given priority to artificial intelligence methods, the application of which can represent a significant development in this field. Recommendations are also given regarding the applicable hardware and data analysis technologies. Data processing is executed on at least four levels from measurement to integrated analysis. We concluded that significant results can be achieved in this field only if the modern tools of computer science and intelligent data analysis are used at all levels.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Rúmen / Doenças dos Bovinos Limite: Animals / Humans Idioma: En Revista: Sensors (Basel) Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Hungria

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Rúmen / Doenças dos Bovinos Limite: Animals / Humans Idioma: En Revista: Sensors (Basel) Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Hungria