Collaborative Research: IDBR: VoxNet--A Deployable Bioacoustic Sensor Network

合作研究：IDBR：VoxNet——可部署的生物声学传感器网络

• 批准号: 0754247
• 负责人: Daniel Blumstein
• 金额: $ 42.26万
• 依托单位: University of California-Los Angeles
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-03-15 至 2012-02-29
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0754247&HistoricalAwards=false
• 关键词: Collaborative; Research; IDBR; VoxNet; Deployable

This award supports a collaborative effort between the PIs and investigators at the University of Arizona and Massachusetts Institute of Technology to design and develop instrumentation for wildlife biologists to inventory animals by detecting, recording, and analyzing their sounds. The system will also allow for field biologists to ask questions about the temporal and spatial dynamics of acoustic communication. Many species produce sounds, and by identifying and localizing them, we can census biodiversity and study the natural dynamics of communication. Typically, these will be vocal sounds, such as bird song, or mammal or frog calls, but in theory, the equipment and algorithms can be used for other sorts of sounds (such as the stridulations of cricket wings). To do so, we must build robust hardware and easy to use software that field biologists can and will use. While there has been the development of ?proof-of-concept? tools and algorithms for many of the components of a usable system, there is no reliable, robust, and easy-to-use system that will permit field biologists to easily census acoustic animals. To do so, a platform called VoxNet will be developed. VoxNet is an integrated software and hardware package which will be a quantum leap forward beyond existing technology in for main areas: software, near-real time event recognition, energy efficiency, and a much longer communication range. VoxNet will be a new, highly integrated, deployable acoustic sensor node with a lower unit cost, and lower energy cost than any existing system. VoxNet will include a highly optimized system software and driver to reduce energy costs through duty cycling. In addition, new 2D/3D algorithms to localize the source of the sound will be developed. These new algorithms will run in near-real-time on a distributed network of VoxNet nodes, enabling users to detect and identify vocalizing animals while in the field. A powerful and easy-to-use software environment based on the WaveScope programming model and the XStream distributed stream processing system (technology partially developed under NSF support at MIT) will be developed. Finally, the system will be tested in the field to both census birds and identify individually alarm calling marmots. The development of tools for field biologists to use will create new ways to census biodiversity, and ask here-to-for impossible or difficult-to-ask questions about the spatial and temporal dynamics of vocal displays. When deployed, we expect these tools to generate novel and important discoveries. The dissemination of these tools will enhance research productivity in behavior, ecology and evolutionary biology. And, these tools will create novel ways to census, conserve, and manage biodiversity. The process of developing these tools will create integrative educational opportunities for undergraduates and graduate students.

该奖项支持亚利桑那大学和麻省理工学院的PI和研究人员之间的合作，为野生生物学家设计和开发仪器，通过检测、记录和分析动物的声音来对动物进行清点。该系统还将允许野外生物学家询问有关声学通信的时间和空间动力学的问题。许多物种都会发出声音，通过识别和定位它们，我们可以普查生物多样性，研究交流的自然动态。通常，这些声音会是声音，比如鸟鸣，或者哺乳动物或青蛙的叫声，但从理论上讲，设备和算法可以用于其他类型的声音(例如板球翅膀的轰鸣)。要做到这一点，我们必须建立强大的硬件和易于使用的软件，田间生物学家可以并将使用这些软件。虽然已经有了概念验证的发展？对于一个可用的系统的许多组件来说，没有可靠的、健壮的和易于使用的系统来允许野外生物学家轻松地对声学动物进行普查。为此，将开发一个名为VoxNet的平台。VoxNet是一个集成的软件和硬件包，它将在主要领域实现超越现有技术的巨大飞跃：软件、近实时事件识别、能源效率和更长的通信范围。VoxNet将是一种新的、高度集成的、可部署的声传感器节点，比任何现有系统的单位成本和能源成本都要低。VoxNet将包括高度优化的系统软件和驱动程序，以通过占空循环降低能源成本。此外，还将开发新的2D/3D算法来定位声源。这些新算法将在VoxNet节点的分布式网络上近乎实时地运行，使用户能够在野外检测和识别发声的动物。将开发一个基于WaveScope编程模型和XStream分布式流处理系统(在麻省理工学院NSF支持下部分开发的技术)的强大且易于使用的软件环境。最后，该系统将在野外进行测试，既能普查鸟类，又能识别单独报警的土拨鼠。野外生物学家使用的工具的开发将创造新的方法来普查生物多样性，并提出关于声音显示的空间和时间动态的不可能或难以提问的问题。部署后，我们预计这些工具将产生新的和重要的发现。这些工具的普及将提高行为学、生态学和进化生物学的研究效率。而且，这些工具将创造新的方式来普查、保护和管理生物多样性。开发这些工具的过程将为本科生和研究生创造综合教育机会。