E-nose herbs recognition system based on artificial neural network technique

Citation

Chow, Kar Kit and Che Soh, Azura and Mohamad Yusof, Umi Kalsom and Ishak, Asnor Juraiza and Hassan, Mohd Khair and Khamis, Shamsul (2013) E-nose herbs recognition system based on artificial neural network technique. In: 2013 IEEE International Conference on Control System, Computing and Engineering (ICCSCE 2013), 29 Nov.-1 Dec. 2013, Penang, Malaysia. (pp. 58-62).

Abstract

Electronic sensing technology intervention was intended to overcome human's physical limitation. It has developed and greatly advanced over the decade. This project emphasizes on characterizing herbs species based on unique of herbs odor. E-nose system in this project consist an array of commercial gas sensor which detects gas through an increase in electrical conductivity when reducing gases are absorbed on the sensor's surface. Data obtained from sensors array are classified using Artificial Neural Network (ANN) technique. The E-nose system with five sensors has the highest capability in classifying herbs sample. Accuracy in classifying the correct herbs increases with number of the sensors used. Results show that sensitivity of E-nose towards herbs classification increases with higher number of sensors.

Download File

Preview

Text (Abstract)
E-nose herbs recognition system based on artificial neural network technique.pdf
Download (35kB) | Preview

Additional Metadata

Item Type:	Conference or Workshop Item (Paper)
Divisions:	Faculty of Engineering Institute of Bioscience
DOI Number:	https://doi.org/10.1109/ICCSCE.2013.6719932
Publisher:	IEEE
Keywords:	Electronic nose; Artificial neural network; Array of sensor; Classification
Depositing User:	Nabilah Mustapa
Date Deposited:	09 May 2019 03:38
Last Modified:	09 May 2019 03:38
Altmetrics:	http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1109/ICCSCE.2013.6719932
URI:	http://psasir.upm.edu.my/id/eprint/68190
Statistic Details:	View Download Statistic

Actions (login required)

View Item