The Research Progress of Vision-Based Artificial Intelligence in Smart Pig Farming

Area of Science:

• Agricultural Science
• Animal Science
• Computer Science

Background:

• Traditional pig farming monitoring is labor-intensive and can negatively impact animal welfare and economic efficiency.
• Increasing pig populations exacerbate the challenges of manual health and welfare monitoring.
• Artificial intelligence (AI) is crucial for developing smart pig farming systems.

Purpose of the Study:

• To review and evaluate AI applications in precision pig farming.
• To analyze AI's role in pig detection, tracking, behavior recognition, and sound recognition.
• To discuss the future opportunities and challenges in precision pig farming.

Main Methods:

• Systematic review of over 150 research papers on precision pig farming.
• Analysis of AI technologies applied to biometric data (sound, behavior) using sensors like cameras and RFID.
• Evaluation of AI's effectiveness in monitoring pig health and welfare indicators.

Main Results:

• AI technologies are effectively applied to pig detection, tracking, behavior, and sound recognition in farming environments.
• Precision farming systems convert real-time biometric data into key indicators of pig health and welfare.
• Early detection of health and welfare issues through AI analysis enables timely interventions.

Conclusions:

• AI integration in pig farming significantly improves health and welfare monitoring capabilities.
• Precision pig farming enhances production efficiency and economic outcomes.
• Addressing the opportunities and challenges of AI is vital for the future of sustainable pig farming.