Mathematical Model of Mastitis Detection Using Milk Data Obtained from Sensors
Keywords:
mastitis, incorporate, diseases, laboratory, coefficientsAbstract
A lot of scientific and research work has been carried out on the detection of mastitis by means of milk data obtained from online sensors of automatic milking systems (AMS) and invasive/non-invasive sensors for animals in livestock farms. In most of these works, mathematical models and algorithms are proposed with different efficiency of mastitis detection as a result of combining certain types of sensor data. However, most farms cannot incorporate enough sensors into their operations due to limited resources and do not conduct laboratory testing activities, which require time, labor and money. This is especially related to animal diseases, which can lead to global problems if timely measures are not taken. In this article, a generalized mathematical model has been developed based on the capabilities of the farm, the effective use of the sensors used in practice, that is, the detection of animal diseases, in particular, mastitis, using sensor data. The originality of the proposed model is that it does not require strict sensor data or indicators related to mastitis. The reason is that, firstly, existing sensor data is processed by linking it to previous historical records, static data, golden rules, and external factors. Secondly, the results of the sensors are summarized by weight coefficients. The result of the model shows the presence of mastitis in the current dairy cow in the [0, 1] interval.
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