Multiple Odor Recognition and Source Direction Estimation with an Electronic Nose System

Kwon, Hyeong-Joon; Kim, Dong-Gyu; Hong, Kwang-Seok

doi:10.1155/2013/361378

Cited by 9 publications

(4 citation statements)

References 16 publications

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“…The estimation accuracy at a single position is not very high for such devices; however, the device accuracy can be improved by acquiring measurements over a number of points. A second approach is to use an array of sensors and estimate the direction of the chemical source from the difference in the reaction times [19][20][21]. Such an approach requires an array of sensors and detectors to obtain data, which results in complicated detection systems.…”

Section: Discussionmentioning

confidence: 99%

Cell-Based Biohybrid Sensor Device for Chemical Source Direction Estimation

2021

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This paper describes a method to estimate the direction from which the signal molecule reaches the sensor by using living cells. In this context, biohybrid sensors that utilize a sophisticated sensing system of cells can potentially offer high levels of chemical-detection sensitivity and selectivity. However, biohybrid-sensor-based chemical-source-direction estimation has not received research attention because the cellular response to chemicals has not been examined in the context of directional information. In our approach, we fabricated a device that can limit the interface between the cell-laden hydrogel and the chemical solution of interest to enhance the time difference over which the chemical solution reaches the cells. Chemical detection by cells that express specific receptors is reflected as the fluorescence of the calcium indicator within the cells. Our device has eight chambers that each house 3D cell-laden collagen hydrogels facing circularly outward. The device also works as a cover to prevent chemicals from permeating the hydrogel from above. In our study, by observing the time course of the fluorescence emission of each chamber, we were able to successfully estimate the chemical-source direction within an error range of 7–13°. Our results suggest that a combination of microstructure devices embedded with living cells can be used to exploit cell functionalities to yield chemical-source directional information.

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Section: Discussionmentioning

confidence: 99%

Cell-Based Biohybrid Sensor Device for Chemical Source Direction Estimation

2021

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“…To validate gas sensors' performance, the experiments were tested in open environment. In most works, the data was obtained using a chamber [58]- [60] where the sensors were placed in and injected sources through a tiny tube. In this research, the experimental source was set as shown in Figure 1(b).…”

Section: Materials and Methods 31 Experimental Setupmentioning

confidence: 99%

Intelligent Sensing Using Metal Oxide Semiconductor Based-on Support Vector Machine for Odor Classification

Husni¹,

Nurmaini²,

Yani³

et al. 2018

IJECE

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Classifying odor in real experiment presents some challenges, especially the uncertainty of the odor concentration and dispersion that can lead to a difficulty in obtaining an accurate datasets. In this study, to enhance the accuracy, datasets arrangement based on MOS sensors parameters using SVM approach for odor classification is proposed. The sensors are tested to determine the sensors' time response, sensors' peak duration, sensors' sensitivity, and sensors' stability when applied to the various sources at different range. Three sources were used in experimental test, namely: ethanol, methanol, and acetone. The gas sensors characteristics are analyzed in open sampling method to see the sensors' performance in real situation. These performances are considered as the base of choosing the position in collecting the datasets. The sensors in dynamic experiment have average of precision of 93.8-97.0%, the accuracy 93.3-96.7%, and the recall 93.3-96.7%. This values indicates that the collected datasets can support the SVM in improving the intelligent sensing when conducting odor classification work.

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“…However, this experiment was also done in simulation. In most other sensor performance tests, the data was taken using a chamber [39]- [41] where the sensors were placed in a chamber and the sources were injected to the chamber using a tube to pass through a tiny in the chamber.…”

Section: Introductionmentioning

confidence: 99%

Metal Oxides Semiconductor Sensors for Odor Classification

Husni

Silvia

Nurmaini

et al. 2017

IJRES

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<span>The performance of gas sensor will differ and vary due to the surrounding environment changing, the way of implementation, and the position of the sensors to the source. To reach a good result on gas sensors implementation, a performance test on sensors is needed. The results of the tests are useful for characterizing the properties of the particular material or device. This paper discusses the performances of metal oxides semiconductor (MOS) sensors. The sensors are tested to determine the sensors' time response, sensors' peak duration, sensors' sensitivity, and sensors' stability of the sensor when applied to the various sources at different range. Three sources were used in experimental test, namely: ethanol, methanol, and acetone. The gas sensors characteristics are analyzed in open sampling method in order to see the sensors' sensitivity to the uncertainty disturbances, such as wind. The result shows that metal oxides semiconductor sensor was responsive to the 3 sources not only in static but also dynamic conditions. The expected outcome of this study is to predict the MOS sensors' performance when they are applied in robotic implementation. This performance was considered as the training datasets of the sensor for odor classification in this research. From the experiments, It was got, in dynamic experiment, the senrors has average of precision of 93.8-97%, the accuracy 93.3-96.7%, and the recall 93.3-96.7%. This values indicates that the sensors were selective to the odor they sensed.</span>

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Multiple Odor Recognition and Source Direction Estimation with an Electronic Nose System

Cited by 9 publications

References 16 publications

Cell-Based Biohybrid Sensor Device for Chemical Source Direction Estimation

Cell-Based Biohybrid Sensor Device for Chemical Source Direction Estimation

Intelligent Sensing Using Metal Oxide Semiconductor Based-on Support Vector Machine for Odor Classification

Metal Oxides Semiconductor Sensors for Odor Classification

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