用AI实时监测风电场附近猛禽，防止撞上风机
BirdRecorder's AI on Sky: Safeguarding birds of prey by detection and classification of tiny objects around wind turbines
- 结合SSD检测与硬件加速，实现800米内实时追踪
- 对红鸢等猛禽检测精度高，响应速度快于现有系统
- 适合风电场生态保护，兼顾可再生能源发展
可再生能源扩张，尤其是风能，正面临与野生动物保护的冲突。为解决这一问题，我们开发了BirdRecorder——一种基于AI的防碰撞系统，用于保护濒危猛禽，特别是红鸢（Milvus milvus）。该系统集成机器人技术、遥测和高性能AI算法，可在800米范围内检测、跟踪并分类鸟类，以减少鸟与风机碰撞。通过采用单次检测（SSD）进行目标识别，并结合专用硬件加速与跟踪算法，系统实现了高精度检测同时满足实时决策需求。本文总结了现场测试结果与性能表现。BirdRecorder在提升能源可持续性的同时促进技术与自然的共存。
原文摘要 · Abstract (English)
The urgent need for renewable energy expansion, particularly wind power, is hindered by conflicts with wildlife conservation. To address this, we developed BirdRecorder, an advanced AI-based anti-collision system to protect endangered birds, especially the red kite (Milvus milvus). Integrating robotics, telemetry, and high-performance AI algorithms, BirdRecorder aims to detect, track, and classify avian species within a range of 800 m to minimize bird-turbine collisions. BirdRecorder integrates advanced AI methods with optimized hardware and software architectures to enable real-time image processing. Leveraging Single Shot Detector (SSD) for detection, combined with specialized hardware acceleration and tracking algorithms, our system achieves high detection precision while maintaining the speed necessary for real-time decision-making. By combining these components, BirdRecorder outperforms existing approaches in both accuracy and efficiency. In this paper, we summarize results on field tests and performance of the BirdRecorder system. By bridging the gap between renewable energy expansion and wildlife conservation, BirdRecorder contributes to a more sustainable coexistence of technology and nature.
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