Multimodal Bird Monitoring System Integrating Micro-Motion Detection and Gimbal Control YOLOv8 Optimization and Laser Deterrence System

Yaping Zhang; Jiayu Pan; Jiaxuan Zhang; Zixuan Li

doi:10.6919/ICJE.202505_11(5).0045

Authors

Yaping Zhang
Jiayu Pan
Jiaxuan Zhang
Zixuan Li

DOI:

https://doi.org/10.6919/ICJE.202505_11(5).0045

Keywords:

YOLOv8 Object Detection; Micro-Motion Detection; DBSCAN; Gimbal Camera Control Algorithm.

Abstract

To mitigate aviation safety risks, agricultural damage, and power outages caused by bird activities, this study introduces a bird recognition and dynamic deterrence system that combines You Only Look Once version 8 (YOLOv8) object detection, advanced micro-motion detection algorithms, and intelligent gimbal control. Traditional bird deterrent methods are often inefficient and lack adaptability, while current detection systems struggle with accuracy and real-time tracking of small, fast-moving targets. By integrating the Lucas-Kanade optical flow technique with the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) clustering algorithm, this research develops a multiscale, adaptive micro-motion detection model that effectively captures subtle bird movements while minimizing noise interference. This model is further enhanced by YOLOv8, utilizing an upgraded Cross-Stage Partial Network to 2-Stage FPN (C2f) architecture, the TaskAlignedAssigner for more accurate sample allocation, and dynamic Mosaic data augmentation for improved detection precision and speed. In addition, a gimbal control algorithm based on spatial registration and adaptive zoom adjustment ensures precise target localization and laser deterrence, employing a two-degree-of-freedom coordinate transformation and a 30x optical zoom field-of-view fitting function.

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