• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.13 no.8
• /
• pp.1679-1686
• /
• 2009

Odor sensing system that is electronic nose device and its signal processing technique has potential to become a critical service for the people who require tangibility of sense of smell in the multimedia communication. PCA(Principal Component Analysis) have been used for dimensionality reduction and visualization of multivariate measurement data. PCA is good for estimating importance value by variance of data but, have some limitation for getting meaningful representation from odor sensing system. This paper explain about how to analyze the data of odor sensing system by ICA(Independent Component Analysis). We show that ICA can give better result like sensor drift analysis, dimensionality reduction and data representation by improved discrimination.

• Journal of Sensor Science and Technology
• /
• v.20 no.3
• /
• pp.151-155
• /
• 2011

A variety of pattern recognition algorithms including neural networks may be applicable to the identification of odors. In this paper, an identification technique for an electronic odor sensing system applicable to wound state monitoring is presented. The performance of the radial basis function(RBF) network is highly dependent on the choice of centers and widths in basis function. For the fine tuning of centers and widths, those parameters are initialized by an ill-conditioned genetic fuzzy c-means algorithm, and the distribution of input patterns in the very first stage, the stochastic gradient(SG), is adapted. The adaptive RBF network with singular value decomposition(SVD), which provides additional adaptation capabilities to the RBF network, is used to process data from array-based gas sensors for early detection of wound infection in burn patients. The primary results indicate that infected patients can be distinguished from uninfected patients.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 1997.04a
• /
• pp.99-102
• /
• 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.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.9 no.6
• /
• pp.101-109
• /
• 2009

The people around industrial complexes and polluted areas suffer from the many occurrences of odors, and frequently issue a request for solving the odors to their local government in charge of those areas. Recently local governments whose regions have a number of such areas have a great interest in monitoring odor occurrences and gathering air on demand. This paper proposes a system in which a user can perform real-time monitoring the values of odor and atmospheric sensors, and the management of odor sensing devices using the Internet browser. Compared to previous systems, the system has an advantage of providing the functions for controlling and managing a number of devices irregardless of the location of the user. Also, the system is built around a blackboard-based multi-process architecture, enabling the easy incorporation of a new software model to be found useful. To our experiment, users showed great satisfactions in terms of the easiness of use. Our system has been installed and operated in an area of a local government in which odors are likely to occur.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.468-471
• /
• 2005

The Air Quality Sensor(AQS), located near the fresh air inlet, serves to reduce the amount of pollution entering the vehicle cabin through the HVAC(heating, ventilating, and air conditioning) system by sending a signal to close the fresh air inlet door/ventilation flap when the vehicle enters a high pollution area. One chip sensor module which include above two sensing elements, humidity sensor and bad odor sensor was developed for AQS (air quality sensor) in automobile. With this sensor module, PIC microcontroller was designed with back propagation neural network to reduce detecting error when the motor vehicles pass through the dense fog area. The signal from neural network was modified to control the inlet of automobile and display the result or alarm the situation. One chip microcontroller, Atmega128L (ATmega Ltd., USA) was used. For the control and display. And our developed system can intelligently detect the bad odor when the motor vehicles pass through the polluted air zone such as cattle farm.

• International Journal of Advanced Culture Technology
• /
• v.5 no.1
• /
• pp.64-69
• /
• 2017

The rapid growth of algae occurs can induce the algae bloom when nutrients are supplied from anthropogenic sources such as fertilizer, animal waste or sewage in runoff the water currents or upwelling naturally. The algae blooms creates the human health problem in the environment as well as in the water resource managers including hypoxic dead zones and harmful toxins and pose challenges to water treatment systems. The algal blooms in the source water in water treatment systems affects the drinking water taste & odor while clogging or damaging filtration systems and putting a strain on the systems designed to remove algal toxins from the source water. This paper propose the emerging In-Situ self-diagnosable smart algae sensing device with wireless connectivity for smart remote monitoring and control. In this research, we developed the In-Site Algae diagnosable sensing device with wireless sensor network (WSN) connectivity with Optical Biological Sensor and environmental sensor to monitor the water treatment systems. The proposed system emulated in real-time on the water treatment plant and functional evaluation parameters are presented as part of the conceptual proof to the proposed research.

• Journal of Institute of Control, Robotics and Systems
• /
• v.13 no.7
• /
• pp.616-623
• /
• 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.

• Journal of Environmental Impact Assessment
• /
• v.4 no.3
• /
• pp.31-39
• /
• 1995

Environmental Impact Assessment (EIA) is composed of various procedures, such as screening, scoping, inventory survey, prediction, assessment, alternative assessment, mitigation measures, and post management. Environmental monitoring data for air quality or water quality, etc. is applied in the EIA process, especially in prediction and post management. As an effective tool of environmental monitoring, the remote sensing method, introduced recently, was used in collecting nationwide data concerning ecosystem and land use. This article explains the current monitoring status in Korea. Monitoring factors include air quality, water quality, soil, ocean, odor, noise, and ecosystems. This report explains the organization of the environmental monitoring system managed by the Ministry of Environment in Korea. Furthermore, it shows the environmental criteria and environmental policies applied to EIA in Korea.

• Journal of Sensor Science and Technology
• /
• v.32 no.3
• /
• pp.194-198
• /
• 2023

With the recent development of industrial technology, the problem of odor due to leakage of toxic gas discharged from industrial complexes is gradually increasing. Among them, hydrogen sulfide is a colorless representative odorous substance that can cause pain through irritation of the mucous membranes of the eyes and respiratory tract, and is a gas that can cause central nervous system paralysis and suffocation when exposed to high concentrations. Therefore, in order to improve the odor problem, research on a gas sensor capable of quickly and reliably detecting a leak of hydrogen sulfide is being actively conducted. A lot of research has been done on the existing metal oxide-based hydrogen sulfide gas sensor, but it has the disadvantage of requiring low selectivity and high temperature operating conditions. Therefore, in this study, a Pt/CNT-based electrochemical hydrogen sulfide gas sensor capable of detecting at low temperatures with high selectivity for hydrogen sulfide was developed. A working electrode capable of selectively detecting only hydrogen sulfide was fabricated by synthesizing Pt nanoparticles as a catalyst on functionalized CNT and applied to an electrochemical hydrogen sulfide gas sensor. It was confirmed that the manufactured Pt/CNT-based electrochemical hydrogen sulfide gas sensor has a current change of up to 100uA for hydrogen sulfide, and the both response time and recovery time were within 15 seconds.

• Journal of Sensor Science and Technology
• /
• v.23 no.2
• /
• pp.99-104
• /
• 2014

Sensor arrays based on chemical sensors produce multidimensional patterns of data that may be used discriminate between different chemicals. For the human observer, visualization of multidimensional data is difficult, since the eye and brain process visual information in two or three dimensions. To devise a simple means of data inspection from the response of sensor arrays, PCA (Principal Component Analysis) or Sammon's nonlinear mapping technique can be applied. The PCA, which is a well-known statistical method and widely used in data analysis, has disadvantages including data distortion and the axes for plotting the dimensionally reduced data have no physical meaning in terms of how different one cluster is from another. In this paper, we have investigated two techniques and proposed a combination technique of PCA and nonlinear Sammom mapping for visualization of multidimensional patterns to two dimensions using data sets from odor sensing system. We conclude the combination technique has shown more advantages comparing with the PCA and Sammon nonlinear technique individually.