In Situ Monitoring of Snowpacks (and Other Harsh Environments) Using Wireless Sensor Networks
Jeff Frolik, University of Vermont
Friday, October 23, 2009, 3:30pm
This seminar is part of the Jones Seminars on Science, Technology, and Society series
Airborne gamma radiation and microwave remote sensing are well-used tools for snowpack monitoring. However, these techniques have shortcomings in terms of resolution (in time and space) and accuracy. As such, ground truth (i.e., in situ) data via snow courses and/or snow pillows/scales is used to complement remote sensing data. Unfortunately, these existing ground-based methods also have significant shortcomings. Snow courses are manually tasking, destructive and have poor time resolution and snow pillows/scales have poor spatial resolution, are invasive to the environment and are costly. Both methods are also limited to terrains that are relatively flat and hazard-free. Our work investigates 'scaling down' microwave and gamma radiation sensing by considering technologies that are lower in cost, lower in power requirements and operate at lower frequencies or energy levels. Our motivation is to ensure these 'sensors' can be integrated with wireless networking hardware in order to form a distributed, monitoring system that can be deployed in a variety of terrains and remotely accessed to retrieve data with arbitrary temporal and spatial resolution. The presentation will discuss our work to date on our SnowMAN project along with future directions. Harsh environments (in the wireless communication sense) are also experienced by sensor networks deployed in cavity structures (e.g., airframes). Our efforts in wireless channel measurements, modeling and emulation for such environs will be discussed. This work has resulted in a new worst-case fading model intended for wireless sensor applications (e.g., predictive maintenance systems aboard aircraft).
About the Speaker
Jeff Frolik is an Associate Professor in the School of Engineering at UVM. He heads the Sensor Network and Wireless (SN*W) Workgroup, a team of faculty and students from engineering and computer science. He is a graduate of the University of Michigan (PhD EE-Systems), University of Southern California (MSEE) and University of South Alabama (BSEE).