###### Abstract  
Analytical and theoretical studies were conducted in working cattle facilities in order to identify infectious, parasitic, and nervous diseases in large horned cattle. Our analytical study was based on the analysis of available scientific research papers. The theoretical research was based on processing the measurement results with existing hardware and software. Both environmental and physiological parameters were obtained from five farms for at least 30 days. The studied cows were divided into two groups. One group consisted of 37 dairy cows of the Holstein breed aged 2-3 years having no clinical signs of disease. All cows in this group were fed the same diet, kept in the same conditions, and had the same lactation period (from 3 to 5 months). Their average weight was 517 (\(\pm\)2.03) kg. For inclusion into the second group, we selected 23 dairy cows with parameters similar to those of the cows in the first group but with some clinical signs of diseases such as encephalomyelitis, infectious enteritis, and hypodermatosis. The data obtained from the animals in the first group were considered as the parameters' standardized boundary values for the estimation of a cow's conditions, i.e., as the norm (the setpoint). As for the data obtained for the second group, they were considered to be deviations from the threshold values of the parameters (deviations from the setpoint, which required a pre-planned action). The analysis was carried out using the program code implemented in the software package \"Matlab R2019b\". We analyzed the correlations between the cows' rumen temperature and pH, their locomotive activity, and environmental parameters such as air temperature and relative humidity in the cowshed. We then constructed graphs of inter-correlating functions. As a result of the study, for the first time, algorithms were compiled enabling the detection of infectious, parasitic, and nervous diseases. clinical assessment of cattle diseases leave much to be desired. On the other hand, the remote early detection of diseases with the aid of advanced technological systems can improve remarkably the accuracy and timeliness of disease detection. In addition, the continuous monitoring of cattle behavior based on advanced technology can provide important information useful for treatment determination or the recognition of a cow state as a temporal event in research of animals' health and well-being [3; 4; 5]. Changes in animals' behavior represent one of the most important criteria for the assessment of animals' well-being and health [6; 7; 8]. The parameters of animals' behavior can be used for the development of a system for the early prevention of diseases. For example, hoot injuries cause lameness, which make cows prefer laying instead of walking, thus decreasing their locomotive activity [9; 10; 11]. A restless behavior of a sick animal can begin prior to the appearance of any of the main clinical symptoms of a disease. For example, cows react less vividly to external stimuli and their activity decreases a few hours before their temperature rises due to mastitis [12; 13]. Besides, the circadian rhythm of cattle's locomotive activity can decrease as early as two days before the clinical symptoms of this disease are detected [14]. Hence, it is possible to use these behavioral deviations as early signs of diseases, detect and treat them at a very early stage, and thus reduce the cost of medicines for cattle. Until recently, it was difficult to detect such changes in behavior on a regular basis; therefore, the employees of livestock farms had to monitor the animals continuously. Today, hi-tech sensors and tools are available for the implementation of the so-called \"precision animal husbandy\". They enable continuous monitoring of the animals' physiological state. Accelerometers can register acts of movement, positioning systems can detect animals' positions, pH meters can measure the acidity of the animals' rumen. and temperature sensors can provide caregivers with additional important health data [15].