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A High Performance, Low Cost, Compact, and Wireless E-nose System for Explosives Detection

Award Information
Agency: Department of Defense
Branch: Army
Contract: W909MY-04-C-0013
Agency Tracking Number: A032-1787
Amount: $70,000.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: A03-109
Solicitation Number: 2003.2
Timeline
Solicitation Year: 2003
Award Year: 2004
Award Start Date (Proposal Award Date): 2003-12-19
Award End Date (Contract End Date): 2004-06-19
Small Business Information
7519 Standish Place, Suite 200
Rockville, MD 20855
United States
DUNS: 161911532
HUBZone Owned: No
Woman Owned: Yes
Socially and Economically Disadvantaged: No
Principal Investigator
 Roger Xu
 Principle Scientist
 (301) 294-5242
 hgxu@i-a-i.com
Business Contact
 Marc Toplin
Title: Director of Contracts
Phone: (301) 294-5215
Email: mtoplin@i-a-i.com
Research Institution
N/A
Abstract

Detection of non-buried explosives is of great significance to both military and homeland security. Although many existing sniffing devices may be used for explosives detection, the size, cost, weight, and portability are primary concern in the development of a field deployable sniffing devices. Herein we propose to build high performance, low cost, compact, and wireless e-nose devices for explosives detection. The system has three key features. First, we have identified an e-nose chip family, developed by Cyrano Sciences, Inc. In addition to small size and low cost, the chip has a wireless capability, which makes the wireless data retrieval possible. Second, we propose to use Support Vector Machines (SVM) to improve the accuracy of explosives classification and nonlinear unmixing for accurate explosive concentration estimation in a mixture. SVM has several attractive advantages and better classification performance than most other classifiers. Most existing unmixing methods are linear in nature. However, our proposed unmixing is a nonlinear approach, which addresses the nonlinear relationship between e-nose responses and different explosive compounds. Finally, we will use a PDA to wirelessly collect the e-nose sensor reading and analyze the data. We believe that our proposed system can find many applications.

* Information listed above is at the time of submission. *

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