Date of Award

Spring 5-2015

Degree Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Computing

School

Computing Sciences and Computer Engineering

Committee Chair

Randy Buchanan

Committee Chair Department

Computing

Committee Member 2

Paige Buchanan

Committee Member 2 Department

Chemistry and Biochemistry

Committee Member 3

Amer Dawoud

Committee Member 3 Department

Computing

Committee Member 4

Zhaoxian Zhou

Committee Member 4 Department

Computing

Committee Member 5

Andrew Sung

Committee Member 5 Department

Computing

Abstract

Selective detection of organic contaminant using widely available and inexpensive metal oxide sensors has the potential to be used in various robotic platforms for navigation, harmful chemical leak detection, mobile environmental monitoring, etc. Selective gas detection in real world environments using easily available sensors has not been reported and can be used in many industries. A sensor system using only four commercially available sensors with accompanying signal conditioning and clustering algorithm capable of discriminatory detection of chemical marker is possible. Tests have shown that temperature, humidity and concentration fluctuations can be accounted for to produce systems for real world environments. An algorithm that accounts for sensor fouling and degradation is produced to achieve a repeatability rate of ninety three percent in a simulated real world environment.

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