A hybrid human sensory mimicking approach: an integrated e-nose and e-tongue system

Taste and smell are two of the five human senses that are common among mammalians. These two senses are usually used together to make up the brain’s perception of flavour. This has lead to the study of data fusion of multiple artificial sensory systems such as electronic nose and electronic tong...

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Main Author: Nazifah, Ahmad Fikri
Format: Thesis
Language:English
Published: Universiti Malaysia Perlis (UniMAP) 2014
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Online Access:http://dspace.unimap.edu.my:80/dspace/handle/123456789/31912
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Institution: Universiti Malaysia Perlis
Language: English
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spelling my.unimap-319122014-02-13T12:48:22Z A hybrid human sensory mimicking approach: an integrated e-nose and e-tongue system Nazifah, Ahmad Fikri Electronic nose Electronic tongue Artificial sensory system Hybrid system Human sensory system Taste and smell are two of the five human senses that are common among mammalians. These two senses are usually used together to make up the brain’s perception of flavour. This has lead to the study of data fusion of multiple artificial sensory systems such as electronic nose and electronic tongue. However, the data fusions performed by these studies are based on separate single-modality systems. Presented is the development of a hybrid system which combines an electronic nose and electronic tongue in a single system. Both sub-system uses off-the-shelf components and developed using rapid prototyping techniques. The hybrid system combines two sensor arrays of MOS gas sensors and ion-selective electrodes. It also consists of a signalcollecting unit and pattern recognition software applied to a computer. The system uses qualitative analysis which is similar to the human sensory system, implementing Principal Component Analysis (PCA) and Artificial Neural Network (ANN). Three tests were performed representing agricultural, environmental and food production applications. The performance of the single-modality systems were compared to the hybrid system. The results show that the hybrid system performed better than the both single sub-systems when appropriate fusion method was used, and able to archive up to 98.67% accuracy. This proved that the multi-modality system performed better in samples discrimination than single-modality system which mimics more closely the human sensory system. 2014-02-13T12:48:22Z 2014-02-13T12:48:22Z 2012 Thesis http://dspace.unimap.edu.my:80/dspace/handle/123456789/31912 en Universiti Malaysia Perlis (UniMAP) School of Mechatronic Engineering
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Electronic nose
Electronic tongue
Artificial sensory system
Hybrid system
Human sensory system
spellingShingle Electronic nose
Electronic tongue
Artificial sensory system
Hybrid system
Human sensory system
Nazifah, Ahmad Fikri
A hybrid human sensory mimicking approach: an integrated e-nose and e-tongue system
description Taste and smell are two of the five human senses that are common among mammalians. These two senses are usually used together to make up the brain’s perception of flavour. This has lead to the study of data fusion of multiple artificial sensory systems such as electronic nose and electronic tongue. However, the data fusions performed by these studies are based on separate single-modality systems. Presented is the development of a hybrid system which combines an electronic nose and electronic tongue in a single system. Both sub-system uses off-the-shelf components and developed using rapid prototyping techniques. The hybrid system combines two sensor arrays of MOS gas sensors and ion-selective electrodes. It also consists of a signalcollecting unit and pattern recognition software applied to a computer. The system uses qualitative analysis which is similar to the human sensory system, implementing Principal Component Analysis (PCA) and Artificial Neural Network (ANN). Three tests were performed representing agricultural, environmental and food production applications. The performance of the single-modality systems were compared to the hybrid system. The results show that the hybrid system performed better than the both single sub-systems when appropriate fusion method was used, and able to archive up to 98.67% accuracy. This proved that the multi-modality system performed better in samples discrimination than single-modality system which mimics more closely the human sensory system.
format Thesis
author Nazifah, Ahmad Fikri
author_facet Nazifah, Ahmad Fikri
author_sort Nazifah, Ahmad Fikri
title A hybrid human sensory mimicking approach: an integrated e-nose and e-tongue system
title_short A hybrid human sensory mimicking approach: an integrated e-nose and e-tongue system
title_full A hybrid human sensory mimicking approach: an integrated e-nose and e-tongue system
title_fullStr A hybrid human sensory mimicking approach: an integrated e-nose and e-tongue system
title_full_unstemmed A hybrid human sensory mimicking approach: an integrated e-nose and e-tongue system
title_sort hybrid human sensory mimicking approach: an integrated e-nose and e-tongue system
publisher Universiti Malaysia Perlis (UniMAP)
publishDate 2014
url http://dspace.unimap.edu.my:80/dspace/handle/123456789/31912
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