Intelligent TNVR Ear-Tag Recognition and Monitoring System for Stray Animal Management

Zhi-Yu Wang; Yung-Hoh Sheu; Bo-Kai Yang; Chi-Jen Chen; Chi-Wen Chen

doi:10.46604/ijeti.2026.15640

Authors

Zhi-Yu Wang Department of Computer Science and Information Engineering, National Formosa University, Yunlin, Taiwan, ROC
Yung-Hoh Sheu Department of Computer Science and Information Engineering, National Formosa University, Yunlin, Taiwan, ROC
Bo-Kai Yang Department of Computer Science and Information Engineering, National Formosa University, Yunlin, Taiwan, ROC
Chi-Jen Chen Department of Computer Science and Information Engineering, National Formosa University, Yunlin, Taiwan, ROC
Chi-Wen Chen Department of Computer Science and Information Engineering, National Formosa University, Yunlin, Taiwan, ROC

DOI:

https://doi.org/10.46604/ijeti.2026.15640

Keywords:

TNVR, stray animal, YOLOv8, image recognition

Abstract

This study aims to enhance stray animal management by improving the efficiency and sustainability of the trap-neuter-vaccinate-return (TNVR) process. An intelligent monitoring system integrating image recognition and radar sensing is proposed for real-time detection and identification. The system utilizes a domain-specific ear-tag recognition model based on OpenCV preprocessing and YOLOv8, achieving an accuracy of 91% under various environmental conditions. Captured data are automatically uploaded via 4G to a centralized server, supporting continuous monitoring and instant alerts. Designed for high-density urban settings, the system mitigates manual workload and enhances decision-making efficiency, contributing to sustainable and humane stray animal control. Although the proposed system demonstrates high detection accuracy and robust performance under real-world conditions, the current evaluation is conducted on a moderate-scale dataset; future work will focus on large-scale deployment and cross-context validation to further examine system generalizability.

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