Low Cost Wireless Remote Sensors for Arctic Monitoring and Lifecycle Assessment
Axiom Data Sciences,
ASRC Federal Mission Solutions,
Alaska Marine Exchange,
University of New Mexico,
University of Texas El Paso
The Arctic is hard to constantly monitor. In order to resolve this problem, low-cost wireless sensors were developed to detect an input event, analyze detected events, and communicate that event data to other sensors in the network. These inexpensive, self-organizing network devices reliably computed and communicated detected human, animal, and environmental events. By utilizing a variety of sensors, it was possible to detect sounds, vibrations, radio and cellphone signals, location, and more based upon the needs of each sensor. When implemented, the project would have provided a quick method to deploy and monitor an Arctic region. Potential uses were events such as ice breakup, environmental events, model validation, vehicle detection in regions of concern, or even assisting with the safety monitoring of personnel and equipment during training exercises.
The project goal is to develop low-cost wireless sensors for use in remote monitoring, asset management, surveillance, and security, particularly in Arctic and marine environments. The team categorizes a sensor’s functionality into three areas: detection of an input event, computation of the detected event, and communication of the data. The team will develop an inexpensive, self-organizing network of devices that can reliably compute and communicate detected events. The computing device for each sensor node is the MoteineoR4 RFM69W and an integrated RFM69 transceiver enables wireless ISM band communications. The team constructed a software simulator and hardware proof-of-concept consisting of a 7x7 array of nodes. The initial target application is to utilize acoustic and electromagnetic signal detectors to classify human vs. animal traffic in a remote area.
The concurrent phase of the project includes the evaluation of the lifecycle cost (LOC) for the deployed sensor array. The team will apply the LOC framework to the monitoring of the US-Canada border for intrusions deployment scenario. The team will assess common techniques in life cycle assessment with focus on geospatial array structure associated with terrain and climate as well as overall power requirements, proximity to urban areas and the end-of-life considerations.
Software Defined Multi-Spectral Imaging for Arctic Sensor Networks
SPIE Proceedings, Volume 9840, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXII [program, h-index], Baltimore, Maryland, April 2016
By: Siewert S., V. Angoth, R. Krishnamurthy, K. Mani, K. Mock, S. B. Singh, S. Srivistava, C. Wagner, R. Claus, M. Vis.