Dertien Jeremy S, Negi Hrishita, Dinerstein Eric, Krishnamurthy Ramesh, Negi Himmat Singh, Gopal Rajesh, Gulick Steve, Pathak Sanjay Kumar, Kapoor Mohnish, Yadav Piyush, Benitez Mijail, Ferreira Miguel, Wijnveen A J, Lee Andy T L, Wright Brett, Baldwin Robert F
Clemson University, Clemson, South Carolina, United States.
RESOLVE, Washington, DC, United States.
Bioscience. 2023 Sep 14;73(10):748-757. doi: 10.1093/biosci/biad076. eCollection 2023 Oct.
The recovery of wild tigers in India and Nepal is a remarkable conservation achievement, but it sets the stage for increased human-wildlife conflict where parks are limited in size and where tigers reside outside reserves. We deployed an innovative technology, the TrailGuard AI camera-alert system, which runs on-the-edge artificial intelligence algorithms to detect tigers and poachers and transmit real-time images to designated authorities responsible for managing prominent tiger landscapes in India. We successfully captured and transmitted the first images of tigers using cameras with embedded AI and detected poachers. Notifications of tiger images were received in real time, approximately 30 seconds from camera trigger to appearing in a smart phone app. We review use cases of this AI-based real-time alert system for managers and local communities and suggest how the system could help monitor tigers and other endangered species, detect poaching, and provide early warnings for human-wildlife conflict.
印度和尼泊尔野生老虎数量的恢复是一项卓越的保护成果，但这也为人类与野生动物之间日益增加的冲突埋下了伏笔，冲突主要发生在公园面积有限以及老虎栖息在保护区之外的地区。我们部署了一项创新技术——TrailGuard AI摄像头警报系统，该系统运行边缘人工智能算法来检测老虎和偷猎者，并将实时图像传输给负责管理印度重要老虎栖息地的指定当局。我们成功地使用嵌入人工智能的摄像头捕捉并传输了老虎的首批图像，还检测到了偷猎者。老虎图像的通知能实时收到，从相机触发到出现在智能手机应用程序中大约只需30秒。我们为管理人员和当地社区回顾了这个基于人工智能的实时警报系统的使用案例，并提出该系统如何能够帮助监测老虎和其他濒危物种、检测偷猎行为以及为人类与野生动物的冲突提供早期预警。
