Theoretical substantiation of the requirements for an intelligent video monitoring system for analyzing the physiological state of cows and predicting its changes

At  the  present  stage  of  development  of dairy farming, the main task facing the industry  is  the  effective  management  of  all processes that ensure the operation of a farm with a large livestock. This task will not be achievable without the use of digital intelligent  production  control  and  management systems, tracking the health of animals and their productivity.  There  are  many  systems that integrate into production and allow you to  monitor  the  health  of  cows  on  a  dairy farm. These systems are based on the identification,  tracking  and  collection  of  information about the physiological state of animals through various sensors. However, all these  systems  are  expensive,  demanding  to maintain, often fail due to aggressive operating conditions. The article considers the possibility of using an intelligent video monitoring system to analyze the physiological state of cows and predict its changes. To substantiate the requirements for an intelligent video monitoring system of the physiological state of cows, a mathematical model of the life of productive cows in the form of a graph of states is proposed. This method graphically displays the possible states of the system and their possible transitions from state to state. Having constructed a graph of states, relying on the central probability theorem for event flows, it is possible to determine the probability and intensity of state transitions using differential equations. For the functioning of the  video  monitoring  system  for  analyzing the physiological state of cows and predicting its changes,  the proposed  mathematical model can be the basis of the system and be based on the collection and analysis of video information  about  animal  behavior.  When covering the entire territory of the animal's living space with video cameras, the intelligent video monitoring system will be able to provide  early  diagnosis  of  changes  in  the physiological state of the observed animals and  issue  a  warning,  which  will  allow  for timely therapeutic and preventive measures.