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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my-unimap-319122014-02-13T12:48:22Z A hybrid human sensory mimicking approach: an integrated e-nose and e-tongue system Nazifah, Ahmad Fikri 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. Universiti Malaysia Perlis (UniMAP) 2012 Thesis en http://dspace.unimap.edu.my:80/dspace/handle/123456789/31912 http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/31912/1/Page%201-24.pdf aca47fa52fa0e4e518e156144c89d4de http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/31912/2/Full%20text.pdf accd9a249322b8114a51543e9073a9b8 http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/31912/3/license.txt 8a4605be74aa9ea9d79846c1fba20a33 Electronic nose Electronic tongue Artificial sensory system Hybrid system Human sensory system School of Mechatronic Engineering |
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Universiti Malaysia Perlis |
| collection |
UniMAP Institutional Repository |
| language |
English |
| topic |
Electronic nose Electronic tongue Artificial sensory system Hybrid system Human sensory system |
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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 |
| granting_institution |
Universiti Malaysia Perlis (UniMAP) |
| granting_department |
School of Mechatronic Engineering |
| url |
http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/31912/1/Page%201-24.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/31912/2/Full%20text.pdf |
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