SIRG: COLLABORATIVE RESEARCH: DeerNet-Wireless Sensor Networking for Wildlife Behavior Analysis and Interaction Modeling

SIRG：协作研究：用于野生动物行为分析和交互建模的 DeerNet-无线传感器网络

• 批准号: 0529082
• 负责人: Zhihai He
• 金额: $ 48万
• 依托单位: University of Missouri-Columbia
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-09-15 至 2009-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0529082&HistoricalAwards=false
• 关键词: SIRG; COLLABORATIVE; RESEARCH; DeerNet; Wireless

AbstractOne of the greatest challenges in understanding the role of free-ranging wildlife in maintaining diversity, tracking invasive species, and the spread of emerging diseases is obtaining unobtrusive visual information required in studying the behaviors and interactions of wildlife species in their environment. The state-of-the-art wildlife monitoring technologies, including radio-tracking and wireless sensor networks, do not provide sampling of animal resource selection, behavior patterns, and the environmental context of the animal's behavior. The central objective of this interdisciplinary award is to bring the video monitoring capability to wireless sensor networks so as to collect important visual information for wildlife behavior analysis and interaction modeling. The overall goal of the research is to develop a long-lived and unobtrusive wildlife video monitoring system capable of real-time video streaming with remote control capability. The captured video in real time will be transmitted over wireless sensor networks to a remote monitoring center for real-time viewing and camera control. Because real-time transmission requirements are particularly challenging to wireless sensor network design, the research will address important issues on energy minimization and performance optimization in video sensing over mobile wireless sensor networks. The PIs will engineer a portable, low-energy, rugged, wireless network video/GPS/motion sensor coupled with an optimized transmission protocols and routing schemes for transferring the video images through sensor node design, access control, and robust routing protocol. Deer-net is a highly innovative interdisciplinary engineering, computer science, and wildlife science project in the field of cognitive ecology. The video monitoring has the potential to significantly advance this area of science and engineering and has broader application to other fields including surveillance, security, process monitoring, and other industrial applications. The broader impacts will arise from multi-disciplinary collaboration among computer scientists, engineers, and wildlife biologists; participation by students spanning undergraduate to doctoral levels; integration into ongoing courses; recruitment of under-represented groups; and educational opportunities for K-12 students to observe wildlife behavior.

摘要在理解自由放养的野生动物在维持多样性、追踪入侵物种和新兴疾病传播中的作用方面，最大的挑战之一是获得研究野生动物物种在其环境中的行为和相互作用所需的不引人注目的视觉信息。最先进的野生动物监测技术，包括无线电跟踪和无线传感器网络，不提供动物资源选择，行为模式和动物行为的环境背景的采样。 该跨学科奖项的中心目标是将视频监控能力引入无线传感器网络，以便收集重要的视觉信息，用于野生动物行为分析和交互建模。本研究的总体目标是开发一种具有远程控制能力的长寿命和不引人注目的野生动物视频监控系统，能够实时传输视频。所捕获的真实的视频将通过无线传感器网络传输到远程监控中心，以进行实时查看和摄像机控制。 由于实时传输的要求是特别具有挑战性的无线传感器网络的设计，该研究将解决重要问题的能量最小化和性能优化的视频感知在移动的无线传感器网络。 PI将设计一种便携式、低能耗、坚固耐用的无线网络视频/GPS/运动传感器，并结合优化的传输协议和路由方案，通过传感器节点设计、访问控制和鲁棒的路由协议传输视频图像。 Deer-net是认知生态学领域的一个高度创新的跨学科工程，计算机科学和野生动物科学项目。 视频监控有可能大大推进这一科学和工程领域，并在其他领域有更广泛的应用，包括监控，安全，过程监控和其他工业应用。 更广泛的影响将来自计算机科学家，工程师和野生动物生物学家之间的多学科合作;学生从本科到博士水平的参与;融入正在进行的课程;招募代表性不足的群体;以及为K-12学生提供观察野生动物行为的教育机会。