SIRG: "Being There": User-centric Wireless Image-based Sensor Networks

SIRG：“Being There”：以用户为中心的基于图像的无线传感器网络

• 批准号: 0428157
• 负责人: Wendi Heinzelman
• 金额: --
• 依托单位: University of Rochester
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-09-01 至 2010-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0428157&HistoricalAwards=false
• 关键词: SIRG; Being; There; User; centric

This Sensor proposal focuses on addressing the limitations of large scale wireless networks ofimaging sensors, namely limitations of sensor power and network bandwidth and human limitationsin the capability to absorb and integrate large amounts of image data. The ideal system providesthe user with an integrated view from the multiple imagers, providing the feeling of being therealong with the capability to navigate the space while allowing the network to run unattended forlong periods of time. Achieving these goals requires a cross-layer design that encompasses all levelsfrom the application to the hardware.Intellectual Merit: We propose developing adaptable low power imagers, distributed imagefusion algorithms, and an overarching sensor management protocol. The imagers will be able tocapture scenes with adaptable resolution, both spatially and in terms of image bit-depth, andperform compression for a fraction of the power required by existing systems. To present theimage data to the user in a more integrated fashion, we will develop image mosaicking algorithmsthat work with uncalibrated cameras and non-planar scenes. Finally, we will develop intelligentsensor management techniques that use application-level information to appropriately configure thesensors and the network itself.Broader Impacts: (1) Providing a being there experience will have a profound impact ondistance-based viewing applications, from surveillance to tele-presence. (2) The PIs are committedto training students and will integrate this research with their teaching. (3) The cross-disciplinarynature of this research and the potential for high societal impact will hopefully attract studentsfrom under-represented groups. (4) The PIs will develop a sensor network tutorial and use thiswith the demonstration image-based sensor network to spark the interest of the community in thisexciting field of study.

该传感器提案的重点是解决成像传感器大规模无线网络的局限性，即传感器功率和网络带宽的限制以及人类吸收和集成大量图像数据的能力的限制。理想的系统为用户提供来自多个成像器的集成视图，提供身临其境的感觉以及导航空间的能力，同时允许网络在无人值守的情况下长时间运行。实现这些目标需要跨层设计，涵盖从应用程序到硬件的所有级别。智力优点：我们建议开发适应性强的低功耗成像器、分布式图像融合算法和总体传感器管理协议。成像仪将能够在空间和图像位深度方面以自适应分辨率捕获场景，并以现有系统所需功率的一小部分进行压缩。为了以更集成的方式向用户呈现图像数据，我们将开发适用于未校准相机和非平面场景的图像镶嵌算法。最后，我们将开发智能传感器管理技术，使用应用程序级信息来适当配置传感器和网络本身。更广泛的影响：（1）提供身临其境的体验将对基于距离的观看应用（从监控到远程呈现）产生深远的影响。 (2) PI致力于培养学生并将这项研究与他们的教学相结合。 (3) 这项研究的跨学科性质和潜在的巨大社会影响将有望吸引来自代表性不足群体的学生。 (4) PI 将开发一个传感器网络教程，并将其与基于图像的传感器网络演示一起使用，以激发社区对这个令人兴奋的研究领域的兴趣。