Vision-Based AI Technologies for Efficient Pig Farming

Pork is an essential component in the world of animal goods. However, there are significant disadvantages to the conventional techniques used to keep an eye on the health and welfare of pigs in farming, such as high labor costs, resource consumption, and time commitment. Using antiquated monitoring methods may be harmful to pig farmers and the animals themselves when the number of pigs grown for farming keeps growing. This may jeopardize the general health and welfare of the pigs in addition to having an effect on the financial results of agricultural operations. With the realization that more advanced methods are required, the use of computational intelligence (AI) has become a crucial component of intelligent pig farming. AI is used in precision pig farming to track biometric data, such pig movement and sound, in real time. By using sophisticated sensors such as RF identification devices and cameras, this data is converted into significant markers of the wellbeing and health of pigs. By using AI, health and welfare concerns may be identified early, allowing for quick intervention and treatment depending on the signs that are examined. Consequently, this raises the pig farming operations' total productivity and financial efficiency. This research offers a thorough review and evaluation of the use of artificial intelligence in pig tracking, analysis of behavior, sound recognition, and detection by critically examining over 150 papers centered on precision pig farming. The investigation comes to a close with a summary and discussion of the benefits and drawbacks of using precision farming methods in pig production.