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.
