Please use this identifier to cite or link to this item: http://ir.unikl.edu.my/jspui/handle/123456789/4884
metadata.conference.dc.title: Odor Recognition Using Fuzzy Logic Algorithm
metadata.conference.dc.contributor.*: Azahar, Ratnawati, I T. M
Shariffah Nur Rasyidah, NurAtiqah Nadiah
metadata.conference.dc.subject: Odor Detection
Gas Sensors
Fuzzy Logic
metadata.conference.dc.date.issued: 27-Nov-2013
metadata.conference.dc.description.abstract: Fuzzy plogic pis pone pof pthe ptechniques pin pArtificial Intelligent p(AI) pthat pwidely pused pto pcontrol penvironmental factors. The effectiveness of fuzzy logic has been proven through a plot pof pcreation pof pIntelligent pSystem pusing pfuzzy plogic a lication. pThis aper resents pthe presearch psegment pof development of methodology for determining odor level using fuzzy logic based algorithm. Two different gas sensors are used which respond to carbon monoxide, methane, hydrogen, ethanol and chlorofluorocarbon. This study focused on evaluating the ossibility of using gas sensor to detect odor level produced by coffee. Sensor fusion is achieved through processing the analog to digital converted values of sensor outputs using algorithm to determine the odor level of predetermined oders. Fuzzy logic algorithm is based on Zadeh-Mamdani type Fuzzy inference system a roach. The result of this study will be displayed in form of ercentage values and will be compared with the simulation result using Matlab.
metadata.conference.dc.description: Conference Venue : UniKL MFI
metadata.conference.dc.identifier.uri: http://ir.unikl.edu.my/jspui/handle/123456789/4884
metadata.conference.dc.conference.name: Science Engineering Technology National Conference (SETNC) 2013
metadata.conference.dc.conference.year: 2013
Appears in Collections:Conference Papers

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