Abstract
If there are errors in the radio frequency identification of animals, during their movement to the group milking plant, information about the fact of the animals entry is lost. The number of the group milking plant stall strictly corresponds to the animal number in the queue, therefore, the information system server receives incorrect information about the correspondence of the animals numbers in the herd to the group milking plant stall numbers. Thus, the results of milking process measured parameters are being obtained with a false correspondence to the animals numbers in the herd. As a result, information related to all animals in the group is lost. To reduce the risk of information loss, group milking plants use means of counting animals during movement. Based on this, in order to obtain reliable information about the measured milking parameters of individual animals at group milking plants, it is necessary to ensure an accurate count of animals during their movement to the stall. Existing means of counting animals, which are based on video analysis, interruption or reflection of the optical radiation flow from animals during movement, do not always ensure their accurate counting. To detect the animals radio frequency identification errors at group milking plants, the method of counting animals is proposed, which is based on optimal linear filtering of the output signal of the animal photoelectric presence sensor. The implementation of the proposed method ensures an increase in the animal counting accuracy, which leads to the effective detection of radio frequency identification errors and an increase in the reliability of information about the measured milking parameters in the group milking plants information systems.
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Kulakov, P. et al. (2024). Method for Counting Animals in Motion for the Milking Plant Information Systems. In: Semenov, A., Yepifanova, I., Kajanová, J. (eds) Data-Centric Business and Applications. Lecture Notes on Data Engineering and Communications Technologies, vol 195. Springer, Cham. https://doi.org/10.1007/978-3-031-54012-7_16
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