• 웰빙융합연구
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• 제6권2호
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• pp.27-31
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• 2023

Purpose: Establishment of a real-time monitoring system for odor control in traditional markets in Gangwon-do and a system for linking prevention facilities. Research design, data and methodology: Build server and system logic based on data through real-time monitoring device (sensor-based). A temporary data generation program for deep learning is developed to develop a model for odor data. Results: A REST API was developed for using the model prediction service, and a test was performed to find an algorithm with high prediction probability and parameter values optimized for learning. In the deep learning algorithm for AI modeling development, Pandas was used for data analysis and processing, and TensorFlow V2 (keras) was used as the deep learning library. The activation function was swish, the performance of the model was optimized for Adam, the performance was measured with MSE, the model method was Functional API, and the model storage format was Sequential API (LSTM)/HDF5. Conclusions: The developed system has the potential to effectively monitor and manage odors in traditional markets. By utilizing real-time data, the system can provide timely alerts and facilitate preventive measures to control and mitigate odors. The AI modeling component enhances the system's predictive capabilities, allowing for proactive odor management.

• Journal of Biosystems Engineering
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• 제29권4호
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• pp.317-322
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• 2004

This study was conducted to evaluate the feasibility of identifying freshness of beef using a surface acoustic wave (SAW) sensor based electronic nose. The beef was stored at 5$^{\circ}C$ and aroma was measured with the passage of time. Chromatographic analysis of the odor showed that number of volatile components and their amounts were rapidly increased after 19 days of storage. Classifying beefs according to their storage days was possible using principle component analysis (PCA). Classifying beefs processed from four different origins was also possible with PCA analysis of odor. This study shows that electronic nose can be applied to beef freshness evaluation and classification of its origin.

• 한국대기환경학회지
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• 제20권6호
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• pp.783-792
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• 2004

In this study, a thick-film semiconductor odor gas sensor for the detection of $CH_3$SH was developed using SnO$_2$ as the main substrate and was investigated in terms of its sensitivity and reaction time. In the process of manufacturing the sensor, Taguchi's design of experiment (DOE) was applied to analyze the effects of a variety of parameters, including the substrate, the additives and the fabrication conditions, systematically and effectively. Eight trials of experiments could be possible using the 27 orthogonal array for the seven factors and two levels of condition, which originally demands 128 trials of experiments without DOE. The additives of Sb$_2$O$_{5}$ and PdCl$_2$ with the H$_2$PtCl$_{6}$ ㆍ6$H_2O$ catalyst were appeared to be important factors to improve the sensitivity, and CuO, TiO$_2$, V$_2$O$_{5}$ and PdO were less important. In addition, TiO$_2$, V$_2$O$_{5}$ and PdO would improve the reaction time of a sensor, and CuO, Sb$_2$O$_{5}$, PdCl$_2$ and H$_2$PtCl$_{6}$ㆍ6$H_2O$ were negligible. Being evaluated simultaneously in terms of both sensitivity and reaction time, the sensor showed the higher performance with the addition of TiO$_2$ and PdO, but the opposite results with the addition of CuO, V$_2$O$_{5}$, Sb$_2$O$_{5}$ and PdCl$_2$. The amount of additives were superior in the case of 1% than 4%. H$_2$PtCl$_{6}$ㆍ6$H_2O$ would play an important role for the increase of sensor performance as a catalyst.nce as a catalyst.

• 제어로봇시스템학회논문지
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• 제13권7호
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• pp.616-623
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• 2007

A dual micro gas sensor array was fabricated using nano sized $SnO_2$ thin films which had good sensitivities to CO and combustible gases, or $H_2S$ gas for air quality sensors in automobile. The already existed air quality sensor detects oxidizing gases and reducing gases, the air quality sensor(AQS), located near the fresh air inlet detected the harmful gases, the fresh air inlet door/ventilation flap was closed to reduce the amount of pollution entering the vehicle cabin through HVAC(heating, ventilating, and air conditioning) system. In this study, to make $SnO_2$ thin film AQS sensor, thin tin metal layer between 1000 and $2000{\AA}$ thick was oxidized between 600 and $800^{\circ}C$ by thermal oxidation. The gas sensing layers such as $SnO_2$, $SnO_2$(pt) and $SnO_2$(+CuO) were patterned by metal shadow mask for simple fabrication process on the silicon substrate. The micro gas sensors with $SnO_2$(+Pt) and $SnO_2$(CuO) showed good selectivity to CO gas among reducing gases and good sensitivity to $H_2S$ that is main component of bad odor, separately.

• International Journal of Advanced Culture Technology
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• 제11권1호
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• pp.325-331
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• 2023

In this paper, we propose a mixed neural network structure of CNN and LSTM that can be used to detect or predict odor occurrence, which is most required in manufacturing industry or real life, using odor complex sensors. In addition, the proposed learning model uses a complex odor sensor to receive four types of data such as hydrogen sulfide, ammonia, benzene, and toluene in real time, and applies this data to an inference model to detect and predict odor conditions. The proposed model evaluated the prediction accuracy of the learning model through performance indicators according to accuracy, and the evaluation result showed an average performance of 94% or more.

• 한국정보통신학회논문지
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• 제13권8호
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• pp.1679-1686
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• 2009

후각 정보의 실감성을 높일 수 있는 멀티미디어 통신 시스템에서 후각정보 전달을 위한 오더(odor) 센싱 시스템 및 관련 신호 처리 기술 개발은 차세대 멀티미디어 산업을 위한 핵심 과제로 떠오르고 있다. 오더 센싱 시스템의 성능 측정에 전통적으로 많이 사용된 방법은 주성분분석(PCA)이다. PCA는 분산에 기반한 도구로서 많은 경우 잘 동작한다. 그러나 오더 센싱 측정 데이터에 대해서는 의미 있는 값을 표시하는 것에 한계가 있다. 이 논문은 독립성분분석(ICA)을 사용하여 오더 센싱 데이터를 분석하는 방법을 설명한다. PCA와 ICA의 차이를 실질적인 측정데이터를 사용하여 비교하도록 한다. 실험을 통해 ICA가 개선된 변별력으로 센서의 경향 분석, 차원축소, 보다 적합한 데이터 표현 등에 있어 PCA보다 나은 결과를 도출함을 보인다.

• International Journal of Advanced Culture Technology
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• 제11권4호
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• pp.464-469
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• 2023

As modern society develops, the number of diseases caused by bad smells is increasing. As it can harm people's health, it is important to predict in advance the extent to which bad smells may occur, inform the public about this, and take preventive measures. In this paper, we propose a hybrid neural network structure of CNN and LSTM that can be used to detect or predict the occurrence of odors, which are most required in manufacturing or real life, using odor complex sensors. In addition, the proposed learning model uses a complex odor sensor to receive four types of data, including hydrogen sulfide, ammonia, benzene, and toluene, in real time, and applies this data to the inference model to detect and predict the odor state. The proposed model evaluated the prediction accuracy of the training model through performance indicators based on accuracy, and the evaluation results showed an average performance of more than 94%.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 1997년도 춘계학술대회 논문집
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• pp.99-102
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• 1997

An electronic nose system is an instrument designed far mimicking human olfactory system. It consists generally of gas (odor) sensor array corresponding to olfactory receptors of human nose and artificial neural network pattern recognition technique based on human biological odor sensing mechanism. Considerable attempts to develop the electronic nose system have been made far applications in the fields of floods, drinks, cosmetics, environment monitoring, etc. A portable electronic nose system has been fabricated by using oxide semiconductor gas sensor array and pattern recognition technique such as principal component analysis (PCA) and back propagation artificial neural network The sensor array consists of six thick film gas sensors whose sensing layers are Pd-doped WO$_3$ Pt-doped SnO$_2$ TiO$_2$-Sb$_2$O$_3$-Pd-doped SnO$_2$ TiO$_2$-Sb$_2$O$_{5}$-Pd-doped SnO$_2$+Pd filter layer, A1$_2$O$_3$-doped ZnO and PdCl$_2$-doped SnO$_2$. As an application the system has been used to identify CO/HC car exhausting gases and the identification has been successfully demonstrated.d.

• 한국화재소방학회논문지
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• 제23권2호
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• pp.1-5
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• 2009

본 연구에서는 분전반의 설치 형태를 조사하였고, 향 검지 시스템의 재현 실험을 통해서 전기 재해 예방의 가능성을 확인하고자 한다. 주택용 분전반 내에 설치된 차단기는 MCCB, RCD 순서로 되어 있으나, 산업용은 혼용되고 있다. 접속이 부적절하게 된 단자대에 가진기를 이용하여 진동을 가했을 때 불꽃이 확인되었다. 단자대에 향 캡슐을 부착하여 실험한 결과, 발생한 열에 의해 캡슐이 정확하게 작동되었다. 센서의 설치 위치에 따라 검지 시간의 차이는 약 10초 이었다. 향 검지 시스템은 전기 설비 사고 예방이 가능한 것으로 판단된다. 전선의 접속부에서 이상 발열이 있을 때 과열의 상태를 관리자에게 경보해 줌으로써 사고 예방이 가능할 것으로 판단된다.

• 센서학회지
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• 제21권4호
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• pp.249-255
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• 2012

Among the human senses, olfactory information still does not have a proper data presentation method unlike that regarding vision and auditory information. It makes presenting the sense of smell into multimedia information impossible, which may be an exploratory field in human computer interaction. In this paper, we propose an olfactory information presentation method, which is a way to use smell as multimedia information, and show an application for scent generation and odor display using a web service. The olfactory information can present smell characteristics such as intensity, persistence, hedonic tone, and odor description. The structure of data format based on olfactory information can also be organized according to data types such as integer, float, char, string, and bitmap. Furthermore, it can be used for data transmitting via a web service and for odor display using a scent generator. The scent generator, which can display information of smell, is developed to generate 6 odors using 6 aroma solutions and a diluted solution with 14 micro-valves and a micropump. Throughout the experiment, we confirm that the remote user can grasp information of smell transmitted by messenger service and request odor display to the computer controlled scent generator. It contributes to enlarge existing virtual reality and to be proposed as a standard reference method regarding olfactory information presentation for future multimedia technology.