Ai-based livestock management system and livestock management method thereof

A livestock management method for an Artificial Intelligence (AI)-based livestock management system including a manager terminal for a livestock stall, a livestock stall control device, and a management server, the livestock management method comprising:

• detecting, through a sensor unit of the livestock stall control device, at least one of a situation of the livestock stall and an abnormal symptom of a plurality of livestock in the livestock stall;
• acquiring, through at least one of an imaging camera and a thermal imaging camera of the livestock stall control device, livestock image data obtained by photographing the plurality of livestock in the livestock stall, in real time;
• receiving, through the management server, the livestock image data from the livestock stall control device in real time;
• separating, through the management server, the plurality of livestock included in the livestock image data into individual objects;
• extracting, through the management server, object information from the livestock image data, the object information including object body temperature information and object behavior information for the individual objects;
• generating, through the management server, determination result data obtained by determining at least one abnormal symptom of at least one livestock in the livestock stall by analyzing standard livestock stall management data and the object information based on deep learning technique;
• transmitting, through the management server, the generated determination result data to the manager terminal in real time;
• and
• controlling, through the management server, the livestock stall control device to change a livestock farming environment of the livestock stall based on the determined at least one abnormal symptom,
• wherein the standard livestock stall management data includes object basic temperature information generated by repeatedly learning highest body temperature information and lowest body temperature information of a normal object which do not have an abnormal symptom and a surrounding object of the normal object, livestock stall basic temperature information generated by repeatedly learning highest temperature information and lowest temperature information of a normal livestock stall and a surrounding livestock stall of the normal livestock stall, and object basic behavior information generated by analyzing normal behavior of the normal object, the standard livestock stall management data being updated based on the determination result data,
• wherein the abnormal symptom of the livestock includes a birthing symptom and a mounting symptom,
• wherein the management server is configured to:
• determine whether the livestock has the abnormal symptom, and classify the abnormal symptom into any one of the birthing symptom and the mounting symptom by using deep learning technique based on the standard livestock stall management data,
• compare and analyze the object body temperature information and the object basic temperature information included in the standard livestock stall management data, and compare and analyze the object behavior information and the object basic behavior information included in the standard livestock stall management data,
• predict birthing situation information including an expected birthing time, a required birthing time, and a number of young objects to be born by monitoring behavior information of a mother object determined as having the birthing symptom,
• generate information on the predicted birthing situation and transmits the information to the manager terminal,
• when predicting the birthing situation, monitor object body temperature information and object behavior information of the young object in consideration of environment information after birthing of the mother object, the environment information including weather information, season information and time information for surroundings of at least one of the mother object and the livestock stall,
• when the young object has an abnormal symptom as a result of the monitoring, transmit a first message notifying that the young object has the abnormal symptom to the manager terminal,
• when it is determined that the mother object delivers the young object in a preset season, a preset weather and a preset time zone based on the environment information, continuously monitor a body temperature of the young object for a preset time of period,
• when the body temperature of the young object is a hypothermia that is less than or equal to a preset temperature as a result of the monitoring, transmit a second message notifying that the young object is a hypothermia to the manager terminal,
• when the body temperature of the young object is less than or equal to a preset temperature, indicating that the young object is a hypothermia, as a result of the monitoring, generate a signal for brightening a lighting of the livestock stall to a preset brightness while raising an internal temperature of the livestock stall to a preset temperature, and transmit the signal to the livestock stall control device,
• predict mounting situation including a number of objects before estrus, an expected time in estrus, a number of expected objects in estrus, and an expected period in non-pregnant condition by monitoring behavior information of an object in estrus determined as having the mounting symptom,
• generate information on the predicted mounting situation and transmits the information to the manager terminal,
• generate a signal capable of enabling the object in estrus and a target object expected to be mounted by the object in estrus to be located in a same space by using the information on the mounting situation and transmit the signal to the livestock stall control device when the object in estrus is determined as having the mounting symptom in case of predicting the mounting symptom.