Recognition System for Awakening and Sleeping by Fuzzy Reasoning

1996 ◽  
Vol 8 (2) ◽  
pp. 167-170
Author(s):  
Takashi Oyabu ◽  
Keyword(s):  
Gas Sensor ◽  
Tin Oxide ◽  
Fuzzy Reasoning ◽  
Recognition System ◽  
Sensor Output ◽  
Human Behaviors ◽  
Compositional Method

Awakening and sleeping are recognized as human behaviors by a gas-sensor output using a fuzzy reasoning. The gas sensor is made from a tin oxide and is sensitive for various gases. The sensor output has a daily periodical pattern. The pattern descends gradually during sleeping and ascends suddenly as of awakening. Recognition is performed using the characteristics of the pattern. At that time, the min-max compositional method is adopted. There are only six rules in this system.

A Bio-Inspired Pattern Recognition System for Tin-Oxide Gas Sensor Applications

2009 ◽  
Vol 9 (6) ◽  
pp. 713-722 ◽  
Author(s):  
Aicha Beya Far ◽  
Farid Flitti ◽  
Bin Guo ◽  
Amine Bermak
Keyword(s):  
Pattern Recognition ◽  
Gas Sensor ◽  
Tin Oxide ◽  
Recognition System ◽  
Pattern Recognition System ◽  
Sensor Applications

scholarly journals A Robust and Low-Complexity Gas Recognition Technique for On-Chip Tin-Oxide Gas Sensor Array

2008 ◽  
Vol 2008 ◽  
pp. 1-6 ◽  
Author(s):  
Farid Flitti ◽  
Aicha Far ◽  
Bin Guo ◽  
Amine Bermak
Keyword(s):  
Gas Sensor ◽  
Tin Oxide ◽  
Sensor Array ◽  
Clustering Algorithm ◽  
Low Complexity ◽  
Recognition System ◽  
Training Data ◽  
Worst Case ◽  
Data Set ◽  
Gas Sensor Array

Gas recognition is a new emerging research area with many civil, military, and industrial applications. The success of any gas recognition system depends on its computational complexity and its robustness. In this work, we propose a new low-complexity recognition method which is tested and successfully validated for tin-oxide gas sensor array chip. The recognition system is based on a vector angle similarity measure between the query gas and the representatives of the different gas classes. The latter are obtained using a clustering algorithm based on the same measure within the training data set. Experimented results on our in-house gas sensors array show more than98%of correct recognition. The robustness of the proposed method is tested by recognizing gas measurements with simulated drift. Less than1%of performance degradation is noted at the worst case scenario which represents a significant improvement when compared to the current state-of-the-art.

scholarly journals Synthesis Sensitive Layer of Ethylene Gas Sensor Based Tin Oxide Nanoparticles Using Water as Solvent In Precipitation Method

2018 ◽  
Vol 159 ◽  
pp. 01060
Author(s):  
Erica Caesariaty Harni Prima Nabena ◽  
Brian Yuliarto ◽  
Nugraha ◽  
Muhammad Iqbal
Keyword(s):  
Gas Sensor ◽  
Tin Oxide ◽  
Water Solution ◽  
Precipitation Method ◽  
Pure Sno2 ◽  
Maturity Level ◽  
Sensitive Layer ◽  
Water As Solvent ◽  
Sno2 Nanoparticle ◽  
Tin Oxide Nanoparticles

Ethylene gas is a gas naturally released by fruits. The maturity level of these fruits could be predicted from the amount of ethylene around them. To maintain the freshness of these fruits, the concentrations of surrounding ethylene need to be monitored. Therefore, suitable gas sensor ethylene were still in progress to get good respond. In this paper systhesis of pure SnO2 nanoparticle from SnCl2.2H2O and water solution in precipitation method was held. The tin oxide powder was obtained in good distribution with nanoparticle size. This nanoparticle powder was formed into thick film, using ethylene glycol as solvant. To observe this sensor characteristics, several test was held in various conditions. Gas testing used pure ethylene gas show better respond at higher than room temperature but recovery time still unsatisfying.

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