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

传感器网络和视频数据流代表了两种成熟的科学观测和数据收集技术，但技术要求截然不同。前者的设计假设了大量的单元和在数据生成率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维持数据记录，通信和存储。 该项目的研究旨在使网络视频摄像机能够在传感器网络的限制下运行：低能耗，远程无系绳设置，以及大空间测量尺度。 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，这些行为的特点是受到人类存在的干扰，位置偏远，需要长时间的等待或需要大而详细的区域覆盖。通过检测、记录和流式传输，在这些环境中进行科学发现，可以扩大我们对环境的理解。该项目涉及开发一种新型低成本视频传感器，该传感器利用从环境中收集的能量进行操作，并支持相机视场的空间和时间子采样。 补充的研究重点包括本地化和合作的网络图像分析，数据压缩和网络路径形成的调查，使视频数据传输到外部观察者，同时最大限度地减少多个流引起的竞争。该项目包括一个示范，使用由50个视频源组成的视频传感器场，在波士顿大学萨金特营地进行试点，观察林地动物，并在与马萨诸塞州大学野外站合作选定的一个沿海地点进行滨鸟和灰海豹研究。

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.