Wednesday, 10 February 2010, Jerry Burman, Sr. Research Scientist, Teledyne Scientific Company presents a look into sensor networks being developed for the military. The Army currently employs heterogeneous unattended ground sensors (UGSs) using a sparse deployment to maximize coverage, minimize pilferage and to monitor terrain bottlenecks. A team consisting of Teledyne Scientific Company, the University of California at Santa Barbara and the Army Research Laboratory (ARL) is developing technologies in support of automated data exfiltration from heterogeneous battlefield sensor networks as part of a US Army contract with the Institute for Collaborative Biotechnologies (ICB).
The ICB program is developing a new system consisting of novel bio-inspired software algorithms for autonomous operations that will leverage proven research to monitor sensor networks from extended ranges, that will collect data in a timely fashion, that will collaboratively control the motion of a sparse network of collectors (e.g. unmanned aerial vehicles) using bio-inspired sampling, that will accurately detect and localize field events and will fuse and classify sensed data. A new bio-inspired event discovery technique will enable fusion of sensor observations at low signal-to-noise ratio without requiring a prior model for the event signature;this is a first step towards sensor networks that are capable of learning.
About the Speaker
Jerry Burman works as a senior research scientist at Teledyne Scientific Company in Thousand Oaks, CA in the Information Science Division. He is the program manager and contributing scientist for a team of researchers in support of the development of advanced bio-inspired systems and sensor networks used to support US Army Research Labs through the Institute of Collaborative Biotechnologies at UCSB. Jerry is a graduate from UCLA with advanced degrees in Mathematics, System Science Engineering and attended a PhD program at Stanford University. He has over a dozen publications and six patents in image and information processing.