AI Keeps An Eye On The ‘Cattle Of The Hills’ — And It Could Change How Farmers Watch Their Herds

Key Highlights:

• ICAR-National Research Centre on Mithun (Nagaland) developed an AI-based system for real-time detection and tracking of Mithun behavior.
• The system monitors four key behaviors: feeding, standing, lying, and mounting, providing insights into animal health and welfare.
• It utilizes the YOLOv8n model for behavior detection and DeepSORT technology for tracking individual animals.
• The technology aims to replace labor-intensive manual observation with continuous, non-contact monitoring, including night vision.

Detailed Insights:

• Mithun (Bos frontalis), known as the "Cattle of the Hills," holds significant social, cultural, and economic importance for tribal communities in Northeast India.
• Changes in animal behavior can provide early indications of health, comfort, nutrition, and physiological conditions.
• The AI framework achieved high accuracy (mean average precision of 99.5%) and real-time processing capabilities (31 frames per second).
• This innovation supports reproductive and oestrus management by identifying mounting behavior.
• Future research will expand the system to identify additional behaviors like aggression and disease-related inactivity.
• The development strengthens precision livestock farming by offering data-driven monitoring solutions for farmers.

Scientific/Technical Concepts Involved:

• Artificial Intelligence (AI): The use of computer systems to perform tasks that typically require human intelligence, such as visual perception and decision-making.
• YOLOv8n: A state-of-the-art, real-time object detection model used here to identify specific animal behaviors.
• DeepSORT: An algorithm designed for multi-object tracking, enabling the system to follow individual animals across video frames.
• Precision Livestock Farming: The application of information and communication technologies to optimize livestock production by monitoring individual animals.