"This thesis focuses on the development of novel schemes for the detection of unintended electromagnetic emissions (UEE) from passive radio frequency (RF) receivers and chemical and biological (CB) agents for the purpose of locating explosive threats (ET) to improve survivability for equipment and personnel in the surrounding environment. The methods and architectures used in this work were developed for use with wireless sensor networks (WSNs). While previous work has shown that highly sensitive equipment is capable of long-range detection of UEE the intention of this work is to develop a network of small, low cost smart sensor nodes (SSNs) capable of short-range detection. Also, the use of zeolite sensors for the detection of CB agents was developed in a similar manner with efforts spent on the integration of the sensor, the routing protocol, and multiple layers of the stackable SSN design. The combination of electromagnetic (EM) and CB detection systems lead to a strategic duet of technologies for the detection of ET through the use of small, low cost WSNs. Experimental results indicate that UEE are detectable from passive circuitry and CB agents can be identified using zeolite sensors"--Abstract, page iii.
Sarangapani, Jagannathan, 1965-
Engineering Management and Systems Engineering
M.S. in Systems Engineering
Air Force Research Laboratory (Wright-Patterson Air Force Base, Ohio)
Leonard Wood Institute
Missouri University of Science and Technology
ix, 60 pages
© 2010 Jake Daniel Hertenstein, All rights reserved.
Thesis - Restricted Access
Library of Congress Subject Headings
Explosives -- Detection
Wireless sensor networks -- Design
Embedded computer systems
Print OCLC #
Electronic OCLC #
Link to Catalog RecordElectronic access to the full-text of this document is restricted to Missouri S&T users. Otherwise, request this publication directly from Missouri S&T Library or contact your local library.http://laurel.lso.missouri.edu:80/record=b10158104~S5
Hertenstein, Jake Daniel, "Detection of explosive threats by using embedded wireless sensor based networks" (2010). Masters Theses. 5997.