At present, there are five main categories of intelligent pig farming technologies.

One is the monitoring and control technology for aquaculture environment. By using intelligent environmental control devices to regulate the pigsty environment, collecting data, analyzing animal behavior’s response to environmental comfort, establishing parameter models and thresholds for evaluating comprehensive environmental comfort, and analyzing the relationship between environmental parameters and feed conversion rate, production performance, etc.

The second is bioinformatics acquisition and behavior monitoring technology. How to use aquaculture big data to analyze animal behavior is currently a research hotspot. Through intelligent weighing, intelligent temperature measurement and other technologies, real-time monitoring of the growth status of live pigs can be achieved, allowing breeders to timely grasp the growth situation of pigs and take corresponding management measures to improve breeding efficiency.

The third is precision feeding management technology. It is characterized by precision, efficiency, and personalized customization, and forms feeding formulas and plans for different breeding objects based on various factors such as animal nutrition, growth status, growth environment, and benefit goals.

The fourth is the decision-making technology for disease prevention and control. How to warn, reduce, and minimize economic losses in aquaculture is an urgent problem that needs to be solved. The use of health inspection robots, epidemic prevention and disinfection robots, and other means can achieve remote diagnosis of diseases. The collected data can also be analyzed through big data to discover problems in a timely manner, which can also help with disease prevention and control supervision at the macro level.

The fifth is the information technology of genetic breeding. Develop a big data cloud platform for pig germplasm resources with a unified computing framework, integrating various forms such as artificial intelligence and machine vision, to provide intelligent services for pig breeding research that combines data-driven and knowledge guidance.

The development goal of intelligent pig farming is to establish a full life cycle breeding process and a nanny style information solution, using information technology and intelligent equipment to achieve scientific management of the entire life cycle of pigs.

Intelligent pig farming requires core businesses such as environment, feeding, disease prevention, behavior analysis, breeding, and waste disposal to achieve interconnectivity, sharing, and co construction of data, solve the needs of pig farming, and improve animal welfare.