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Development and Implementation of an IoT-Enabled Smart Poultry Slaughtering System Using Dynamic Object Tracking and

Hao-Ting Lin¹, Suhendra^2,3

¹Department of Bio-Industrial Mechatronics Engineering, National Chung Hsing University, 145 Xingda Rd., South Dist., Taichung City 402, Taiwan.

Sensors (Basel, Switzerland)

|August 28, 2025

Summary

This study developed an AI-powered system using YOLO-v4 for humane poultry slaughter. The smart system accurately identifies stunned and unstunned red-feathered chickens, enhancing animal welfare and processing efficiency.

Keywords:

IoT dynamic tracking object image recognition poultry slaughter

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Area of Science:

Agricultural Engineering
Artificial Intelligence
Animal Welfare Science

Background:

Increasing demand for humane and efficient poultry slaughter methods.
Limitations of traditional manual inspection and existing electrical stunning methods for specific breeds.
Need for specialized systems for red-feathered Taiwan chickens.

Purpose of the Study:

To implement a smart, safe, and humane slaughtering system for red-feathered Taiwan chickens.
To integrate an IoT-enabled vision system for real-time monitoring and management of poultry stunning.
To enhance animal welfare and processing efficiency through AI-driven object recognition.

Main Methods:

Development of a dynamic object tracking recognition system using the YOLO-v4 model for chicken morphology feature extraction.
Integration of IoT modules for real-time monitoring, sensor-based classification, and cloud decisions.
Application of image amplification techniques to improve model performance.

Main Results:

The YOLO-v4 model achieved high accuracy in identifying stunned (99%) and unstunned (89%) chickens after image amplification.
The system demonstrated a mean average precision (mAP) of 94% at an IoU threshold of 0.75 and processed images at 39 frames per second.
The YOLO-v4 model outperformed the YOLO-X model in transient stability for poultry slaughter recognition.

Conclusions:

The developed smart slaughtering system is a practical and scalable AI application for the poultry industry.
The system effectively enhances animal welfare and processing efficiency for red-feathered Taiwan chickens.
Real-time monitoring and AI-based recognition are crucial for modern, humane poultry processing.