LIVEMOS-G: A High Throughput Gantry Monitoring System with Multi-Source Imaging and Environmental Sensing for...

Area of Science:

• Agricultural Engineering
• Animal Science
• Computer Vision

Background:

• High-density livestock farming, particularly rabbit farming, faces challenges in efficient health and environmental monitoring.
• Traditional manual inspection methods are labor-intensive, error-prone, and unsuitable for real-time management in large-scale operations.

Purpose of the Study:

• To develop an intelligent, automated monitoring system for large-scale rabbit farms.
• To address limitations in timely health inspection and environmental monitoring.
• To enhance biosecurity, animal welfare, and data-driven management in modern rabbit farming.

Main Methods:

• Development of the Livestock Environmental Monitoring System-Gantry (LIVEMOS-G), a gantry-based system with a three-axis motion module.
• Integration of multi-source imaging (RGB, depth, near-infrared, thermal infrared) and environmental sensing.
• Autonomous farm inspection, data collection, and application of a fusion-based object detection model trained on a dataset of 2325 image sets to detect deceased rabbits.

Main Results:

• The system autonomously inspects farms, capturing multi-angle, high-resolution images and environmental data without disturbing animals.
• Accurate collection and comparison of environmental parameters with welfare standards.
• Successful detection of dead rabbits using the developed object detection model.

Conclusions:

• LIVEMOS-G provides a scalable, non-intrusive solution for intelligent livestock inspection in high-density rabbit farms.
• The system contributes to improved biosecurity, animal welfare, and data-driven farm management.
• The technology shows potential for adaptation to other livestock species, supporting sustainable agriculture.