UPM Institutional Repository

Selection of feature analysis electronic nose signals based on the correlation between gas sensor and herbal phytochemical


Citation

Mohamad Yusof, U. K. and Che Soh, Azura and M. Radzi, N. F. and Ishak, Asnor Juraiza and Hassan, Mohd Khair and Ahmad, Siti Anom and Khamis, Shamsul (2015) Selection of feature analysis electronic nose signals based on the correlation between gas sensor and herbal phytochemical. Australian Journal of Basic and Applied Sciences, 9 (5). pp. 360-367. ISSN 1991-8178; ESSN: 2309-8414

Abstract

Background: Electronic nose consists of commercial gas sensor which detects gas through an increase in electrical conductivity when reducing gases are adsorbed on the sensor's surface. The election of the best gas sensor that suits to the target gas detection is very crucial in order to capture the desired signal to be used in further process to design e-nose for odor detection with high rate of classification. In this study, five herbs were chosen as sample for electronic nose development. The volatile chemical compound in herbs as the source of the odor will be characterized by using gas chromatography–mass spectrometry test. The result of the test is useful to determine the potential gas sensor for e-nose. The process is followed by one to five feature analysis of the e-nose signal to find the best gas sensor array. Objective: The selection of gas sensors is investigated in order to design e-nose for odor detection. Results Feature analysis shows that five feature analyses by using five types of gas sensor for e-nose give the best result as the 90% accuracy of classification. Conclusion: Five types of gas sensors have been determined from the phytochemical’s results of GCMS test. Hence, it will be used as sensor array in e-nose application for herbs classification.


Download File

[img] Text
Selection of feature analysis electronic nose signals based on the correlation between gas sensor and herbal phytochemical.pdf

Download (85kB)
Official URL or Download Paper: http://www.ajbasweb.com/old/ajbas_March_2015.html

Additional Metadata

Item Type: Article
Divisions: Faculty of Engineering
Institute of Bioscience
Publisher: American-Eurasian Network for Scientific Information (AENSI) Publications
Keywords: Gas sensor; Electronic nose; Gas chromatography-mass spectrometry; Herbs classification
Depositing User: Ms. Ainur Aqidah Hamzah
Date Deposited: 16 Jun 2022 08:37
Last Modified: 16 Jun 2022 08:37
URI: http://psasir.upm.edu.my/id/eprint/46250
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item