NeTS-NOSS: Localized Computation and Network Path Formation to Enable Pervasive Video Sensing

NeTS-NOSS：本地化计算和网络路径形成以实现普遍的视频传感

• 批准号: 0721884
• 负责人: Thomas Little
• 金额: --
• 依托单位: Trustees of Boston University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-01 至 2011-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0721884&HistoricalAwards=false
• 关键词: NeTS; NOSS; Localized; Computation; Network

Sensor networking and video data streaming represent two maturing technologies for scientific observation and data collection with very different technical requirements. The former is designed assuming large numbers of units and long-term deployment in settings with small data generation rates. The latter can provide rich visual detail in collected data but requires significant energy resources to sustain data recording, communication, and storage. The research in this project seeks to enable networked video cameras to operate within sensor network constraints: at low energy consumption, in remote un-tethered settings, and in large spatial measurement scales. The work is motivated by collaborations with ecologists and biologists that reveal many opportunities for the observation of species behavior that are characterized by events that are disturbed by human presence, are remotely sited, require long periods of waiting or require large, detailed area coverage. Detecting, recording, and streaming to enable scientific discovery in these settings can expand our understanding of the environment.The project involves the development of a novel low-cost video sensor that operates on energy harvested from the environment and supports spatial and temporal sub-sampling of the camera field of view. Complementary research thrusts include the investigation of localized and cooperative in-network image analysis, data compression, and network path formation to enable delivery of video data to an outside observer while minimizing contention caused by multiple streams. The project includes a demonstration using a video sensor field comprised of 50 video sources in pilots involving the observation of woodland animals at Boston University's Sargent Camp and in the study of shorebirds and grey seals at a coastal site selected in collaboration with the University of Massachusetts Field Station.

传感器网络和视频数据流代表着两种成熟的科学观测和数据采集技术，它们的技术要求截然不同。前者的设计假设了大量单元和在数据生成率较低的环境中的长期部署。后者可以在收集的数据中提供丰富的视觉细节，但需要大量的能源来支持数据记录、通信和存储。该项目的研究旨在使网络摄像机能够在传感器网络的限制下运行：低能耗、远程非连接环境和大空间测量范围。这项工作的动机是与生态学家和生物学家的合作，揭示了许多观察物种行为的机会，这些行为的特征是受人类存在干扰的事件、偏远的事件、需要长时间等待或需要大范围、详细区域覆盖的事件。通过检测、记录和串流来实现这些环境中的科学发现，可以扩大我们对环境的理解。该项目涉及开发一种新型的低成本视频传感器，该传感器利用从环境中获取的能量进行操作，并支持相机视野的空间和时间亚采样。补充性研究工作包括调查本地和协作的网络内图像分析、数据压缩和网络路径形成，以便能够将视频数据交付给外部观察者，同时最大限度地减少由多个流引起的争用。该项目包括使用由50个视频源组成的视频传感器场进行演示，在波士顿大学萨金特营地的飞行员中观察林地动物，并在与马萨诸塞大学野外站合作选择的沿海地点对滨鸟和灰海豹进行研究。