首个多模态野生动物监测数据集，支持物种识别与生态研究。
SmartWilds: Multimodal Wildlife Monitoring Dataset
- 同步采集无人机影像、相机陷阱与声学数据
- 覆盖220英亩牧场，四天多模态数据验证互补性
- 适合生态监测、计算机视觉与保护研究者使用
我们发布了首个SmartWilds多模态野生动物监测数据集。该数据集包含2025年夏季在俄亥俄州野生公园采集的无人机影像、相机陷阱照片与视频、以及生物声学记录，实现三模态同步。数据覆盖220英亩牧场，包含戴维鹿、四川扭角羚、普氏野马及本地物种，持续四天。本研究对比了不同传感器模态在土地利用模式、物种检测、行为分析和栖息地监测中的表现，验证其互补优势。研究建立可复现的多模态监测流程，并开放数据以推动保护计算机视觉研究。未来版本将加入标记个体的同步GPS追踪数据、公民科学数据及跨季节扩展数据。
原文摘要 · Abstract (English)
We present the first release of SmartWilds, a multimodal wildlife monitoring dataset. SmartWilds is a synchronized collection of drone imagery, camera trap photographs and videos, and bioacoustic recordings collected during summer 2025 at The Wilds safari park in Ohio. This dataset supports multimodal AI research for comprehensive environmental monitoring, addressing critical needs in endangered species research, conservation ecology, and habitat management. Our pilot deployment captured four days of synchronized monitoring across three modalities in a 220-acre pasture containing Pere David's deer, Sichuan takin, Przewalski's horses, as well as species native to Ohio. We provide a comparative analysis of sensor modality performance, demonstrating complementary strengths for landuse patterns, species detection, behavioral analysis, and habitat monitoring. This work establishes reproducible protocols for multimodal wildlife monitoring while contributing open datasets to advance conservation computer vision research. Future releases will include synchronized GPS tracking data from tagged individuals, citizen science data, and expanded temporal coverage across multiple seasons.
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