Suziyanti, Zaib and Muhammad Sharfi, Najib and Suhaimi, Mohd Daud and Muhammad Faruqi, Zahari and Mujahid, Mohamad The study of groundwater source by using KNN classification. In: The 6th International Conference on Electrical, Control and Computer Engineering (InECCE2021) , 23rd August 2021 , Microsoft Teams platform. pp. 1-12.. (Unpublished)
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Abstract
This study was focused on assessing the groundwater as a source using odor by electronic nose (E-nose). Water is a finite resource that essential for humans and ecosystem existence. The suitable quality water resources need to be paid attention since it controlled by naturalistic activities such as geology, motion of groundwater, and water-rock interaction. In general, it is tasteless, odorless, and nearly colorless liquid but in other aspect, it also fulfills the need of minerals in human body up to a certain limit. The anthropogenic activities had caused an imbalance of these minerals in water that result in degradation of its quality. The aim of this study to apply an E-nose in classification of water and to identify odor pattern. It consists of sensor array which mimic the olfactory receptor in human nose that ability to sniff volatile odor that usually undetectable by human nose. K-Nearest Neighbor (KNN) is applied in performing the intelligent classification with mean feature data as an input. The finding results shows that the E-nose sensitivity, specificity and accuracy indicates at 100% for Euclidean distance.
| Item Type: | Conference or Workshop Item (Lecture) |
|---|---|
| Uncontrolled Keywords: | Groundwater; Tube well; E-Nose; Odor pattern; Mean data feature; Intelligent classification; K-Nearest Neighbors |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering T Technology > TS Manufactures |
| Faculty/Division: | Institute of Postgraduate Studies Faculty of Manufacturing and Mechatronic Engineering Technology |
| Depositing User: | Mrs Norsaini Abdul Samat |
| Date Deposited: | 07 Dec 2021 07:26 |
| Last Modified: | 07 Dec 2021 07:26 |
| URI: | http://umpir.ump.edu.my/id/eprint/32766 |
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