Detection of oil pollution in seawater: Biosecurity prevention using electronic nose technology

Author

Chandler, Rob ; Das, Aruneema ; Gibson, Tim ; Dutta, Ritaban

Author_Institution

AutoNose Manuf. Ltd., Leeds, UK

fYear

2015

fDate

13-17 April 2015

Firstpage

98

Lastpage

100

Abstract

In this paper-conducting polymer gas sensor based AutoNose electronic nose (E-Nose) technology has been used for detection of oil contamination in seawater samples. AutoNose E-nose is a headspace analyzer based on six conducting polymer sensors. Seawater samples with known (or induced) oil contamination were tested and classified against the unpolluted seawater samples using machine learning based ensemble classifiers with very high accuracy. We show that a simple headspace sensing E-Nose could be used to rapidly detect oil pollution in seawater for early biosecurity prevention.

Keywords

conducting polymers; electronic noses; learning (artificial intelligence); marine safety; oil pollution; pattern classification; seawater; AutoNose e-nose; AutoNose electronic nose; biosecurity prevention; conducting polymer gas sensor; electronic nose technology; headspace analyzer; machine learning based ensemble classifiers; oil contamination detection; oil pollution detection; unpolluted seawater; Chemical sensors; Chemicals; Electronic noses; Neural networks; Nose; Polymers; Sensors; biosecurity; conducting polymer gas sensor; electronic nose; ensemble classifier; machine learning;

fLanguage

English

Publisher

ieee

Conference_Titel

Data Engineering Workshops (ICDEW), 2015 31st IEEE International Conference on

Conference_Location

Seoul

Type

conf

DOI

10.1109/ICDEW.2015.7129554

Filename

7129554