IIBR Instrumentation: Coordinated innovations in radio telemetry (CIRT) for wildlife

北亚利桑那大学获得了一项奖励，通过跨多个技术领域的协调创新，推进野生动物遥测数据收集和标签检测。小型鸟类和动物是生态系统中的重要角色。在世界许多地区，它们的数量正在下降，但原因尚不清楚，这促使人们采取方法追踪它们的位置和栖息地。然而，获得关于小型野生动物位置和活动的高保真数据仍然是一个挑战。除了最小和最简单的遥测设备或标签外，它们的小尺寸排除了所有设备。指南建议70%的蝙蝠、鸟类和陆生物种携带的标签重量应分别低于0.75 g、4.4g和12.5 g，大约相当于1到10个回形针的质量。这些质量限制继续决定使用微型甚高频（VHF）无线电发射机进行小物种定位。此外，由于成本限制，对较大物种的研究通常继续依赖甚高频无线电标签。从这些小甚高频标签发射的无线电脉冲是非常具有挑战性的检测和定位。该研究将提高野生动物遥测数据的质量，促进对运动和行为的时空理解。已开发的技术将开放来源，使野生动物生物学和生态学研究界能够采用，并通过野生动物专业人员研讨会进行传播。此外，提高公众意识是该项目的核心目标；这将通过参与社区和K-12教育推广计划来实现。这项研究将开发一种最佳的标签检测算法和软件实现，使自动检测成为可能，同时保持与传统跟踪接收器的兼容性。这些方法将提高接收范围，并使遥测设备的自动检测成为可能。标签将被重新设计为使用新的无线系统芯片技术和传输方法，以提高检测范围和可靠性，并使与研究人员的现场互动成为可能。最后，研究将为人类跟踪器和基于无人机（UAV）的跟踪系统开发运动引导方法，以减少检测和定位的时间和精力。这三个研究重点将相互协调，以优化整体数据收集速度和质量。由此产生的算法和集成系统将进行实验室和现场测试，以定量性能标准和成功度量来展示结果。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

An award is made to Northern Arizona University to advance wildlife telemetry data collection and tag detection through coordinated innovation across multiple technological domains. Small birds and animals are important actors in ecosystems. Their populations are declining in many areas of the world, but the causes are not well-understood, motivating methods to track their locations and habitats. However, obtaining high fidelity data on the location and activity of small wildlife continues to be a challenge. Their small size precludes all but the smallest and most simple telemetry devices, or tags. Guidelines suggest that 70% of bats, birds and terrestrial species should carry tags that weigh less than 0.75 g, 4.4g, and 12.5 g, respectively—about the mass of 1 to 10 paper clips. These mass constraints continue to dictate the use of tiny Very High Frequency (VHF) radio transmitters for small-species localization. Moreover, studies of larger species often continue to rely upon VHF radio tags due to cost constraints. The transmitted radio pulses from these small VHF tags are very challenging to detect and localize. This research will improve the quality of wildlife telemetry data and advance the spatiotemporal understanding of movement and behavior. The developed technology will be open-sourced to enable adoption by the wildlife biology and ecology research communities, with dissemination through a workshop for wildlife professionals. Additionally, increasing public awareness is a core goal of this program; this will be achieved through participation in community and K-12 educational outreach programs. This research will develop an optimal tag detection algorithm and software implementation that will enable automated detection while maintaining compatibility with legacy tracking receivers. These methods will improve the range of reception and enable automated detection of telemetry devices. Tags will be reconceived to use both new wireless-system-on-chip technology and transmission methods to improve detection range and reliability, and enable in-the-field interaction with researchers. Finally, the research will develop movement guidance methods for both human trackers and unmanned aerial vehicle (UAV)-based tracking systems to reduce detection and localization time and effort. The efforts in these three research foci will be coordinated to optimize overall data collection speed and quality. The resulting algorithms and integrated systems will be lab and field tested to demonstrate outcomes with quantitative performance criteria and success metrics.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.