The goal of this project was to construct a proof-of-concept visible two channel (optional visible + long wave infrared multispectral) camera proof of concept to be tested at the Port of Anchorage. The proof-of-concept was to be constructed using all off-the-shelf hardware components and used to form a baseline of comparison for the longer term Computational Photometer (“Smart-Cam”) for a longer term goal of the research, for Arctic operations with drop-in-place multi-spectral and stereo vision cameras. From the proof-of-concept it was expected that challenges of long term battery operations, drop-in-place packaging for Arctic environments, and power efficiency and methods to recharge can be better understood for follow-on phases. Potential uses were for oil detection under ice in an AUV and tracking and detecting vessels, animals, and people in fog and ice environments typical of the Arctic.
The goal of the SmartCam project is to construct a power efficient (less than 10 Watt peak) three channel (visible + long wave infrared) camera system. The SmartCam integrates all off-the-shelf optics, computing and detectors, so it is defined by software and the system design. Unlike traditional cameras that either stream live video for remote analysis or simply store data for post analysis, the SmartCam system can perform image processing on the camera itself in real time to save the most salient images, pre-processed for efficient opportunistic download or uplink to the “cloud.”
The processing can provide passive 3D mapping, fusion of thermal images with visible and provide low-light and night vision. The software-defined multi-spectral imaging is hypothesized to enable collection of salient security and safety images with greater efficiency and will be compared directly to continuous image archives also taken by SmartCam (continuous 1-to-30 Hz). Overall, key performance metrics for the SmartCam are total power used (total energy consumed in Watt/hours) as well as the number of false and correct positive and negative images collected.
Image and Information Fusion Experiments with a Software-Defined Multi-Spectral Imaging System for Aviation and Marine Sensor Networks
AIAA SciTech 2017 [program], Grapevine, Texas, January 2017
By: Siewert S., M. Vis, R. Claus, R. Krishnamurthy, S. B. Singh, A. K. Singh, S. Gunasekaran
Low Cost, High Performance and Efficiency Computational Photometer Design
SPIE Sensing Technology and Applications, SPIE Proceedings, Volume 9121, Baltimore, Maryland, May 2014
By: Siewert S., J. Shihadeh, Randall Myers, Jay Khandhar, Vitaly Ivanov