• Journal of KIISE
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• v.42 no.2
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• pp.255-263
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• 2015

The sensor registry system has been developed for instant use and seamless interpretation of sensor data in a heterogeneous sensor network environment. However, the existing sensor registry system cannot provide information for interpretation of the sensor data in situations in which the network is unstable. This limitation causes several problems such as sensor data loss, inaccuracy of processed results, and low service quality. A method to resolve such problems in the aspect of software is presented herein. In other words, an extended sensor registry system is proposed to enable the stable use of sensor information, even under conditions of unstable network connection, by providing sensor information with a mobile device in advance through the user path prediction. The results of experiments and evaluation are also presented. The extended sensor registry system proposed in this paper enhances the stable usability of sensor information as well as improves the quality of sensor-based services.

• Journal of the Korea Society of Computer and Information
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• v.18 no.8
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• pp.105-111
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• 2013

This paper presents a virtual sensor system that is an effective method to test application software of smart sensors. The common way of testing sensor application is to build a test board, connect sensors to the board, and test sensor applications on the board with sensor's measurements as inputs. The problem of testing sensor application software with sensor's measurements as inputs is the restriction of test data. In other words, software testers cannot manipulate test data, because test data is generated by sensors. To solve this problem a virtual sensor system is presented in this paper. The virtual sensor system enables software testers to manipulate measurements of sensors. In the virtual sensor system, generation of virtual sensors comprises three stages - sensor selection, sensor characterization, and determination of output patterns. Sensor's measurements that can be manipulated through the virtual sensor system make the process of testing efficient. To show the usefulness of our virtual sensor system, it is applied to sensor applications in Android platform and the result of experiments is shown.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.318-321
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• 2003

In case, sensor system performs where it is difficult to access physically and it is in the poor environment, it is limited to communicate by using wire and installing power module in sensor system. In this paper, it suggests how information is obtained from telemetry sensor by means of inductive coupling without battery. Comparing with the telemetry sensor system of inductive coupling by the power supply, this system estimates the capacitance of sensor with high precision in using RLSE, not the process of modulation and demodulation. In order to activate this system, inductive model is used and in case of time variant parameter, telemetry sensor system which has got high rate in accuracy is implemented by using the forgetting factor.

• Journal of Korea Multimedia Society
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• v.13 no.6
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• pp.890-900
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• 2010

The Bayesian networks methods provide an efficient tool for performing information fusion and decision making under conditions of uncertainty. This paper proposes Bayes estimators for the system effectiveness in energy saving of the wireless sensor networks by use of the Bayesian method under the non-informative prior knowledge about means of active and sleep times based on time frames of sensor nodes in a wireless sensor network. And then, we conduct a case study on some Bayesian estimation models for the system energy saving effectiveness of a wireless sensor network, and evaluate and compare the performance of proposed Bayesian estimates of the system effectiveness in energy saving of the wireless sensor network. In the case study, we have recognized that the proposed Bayesian system energy saving effectiveness estimators are excellent to adapt in evaluation of energy efficiency using non-informative prior knowledge from previous experience with robustness according to given values of parameters.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.499-500
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• 2007

The various sensor nodes operating in Ubiquitous Sensor Network environment require the tiny Operating System different from the existing pc-type operating system because of their characteristics. Also Sensor Network operating system needs to support the rapid event handling which sensor node must implement. In this paper, we overcome the drawbacks of the existing sensor network operating system and propose the new kernel which is designed to assist developer to construct event-central operating system entirely. We also evaluate the performance of the super tiny sensor network operating system based on proposed kernel, comparing with that of the existing sensor network operating system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.8
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• pp.1130-1133
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• 2021

In this paper, a miniaturized sensor interface circuit for the respiration detection system is proposed. Respiratory diagnosis is one of the main ways to predict various diseases. The proposed system consists of respiration detection sensor, temperature sensor, and interface circuits. Electrochemical type gas sensor using solid electrolytes is adopted for respiration detection. Proposed system performs sensing, amplification, analog-to-digital conversion, digital signal processing, and i2c communication. And also proposed system has a small form factor and low-cost characteristics through optimization and miniaturization of the circuit structure. Moreover, technique for sensor degradation compensation is introduced to obtain high accuracy. The size of proposed system is about 1.36 cm².

• JSTS:Journal of Semiconductor Technology and Science
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• v.17 no.2
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• pp.186-191
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• 2017

An integrated pressure-sensor system was developed using the sensor-conditioning processes, which resulted in the optimum sensitivity of the pressure-sensor through the signal amplification, noise reduction, and level shift. Due to the specified characteristics among the components, such as operation range, the sensor output was generally limited compared to the full scale of the reading when coupled with other parts. Devices fabricated exhibited comparable characteristics with higher pressure sensitivity to that of the pressure sensor without sensor-conditioning process. In this work, the sensor resolution was at least enhanced at least by 25% using the sensor-conditioning processes.

• International journal of advanced smart convergence
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• v.6 no.3
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• pp.29-37
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• 2017

The current behavior recognition system don't match data formats between sensor data measured by user's sensor module or device. Therefore, it is necessary to support data processing, sharing and collaboration services between users and behavior recognition system in order to process sensor data of a large capacity, which is another formats. It is also necessary for real time interaction with users and behavior recognition system. To solve this problem, we propose fog cloud based behavior recognition system for human body sensor data processing. Fog cloud based behavior recognition system solve data standard formats in DbaaS (Database as a System) cloud by servicing fog cloud to solve heterogeneity of sensor data measured in user's sensor module or device. In addition, by placing fog cloud between users and cloud, proximity between users and servers is increased, allowing for real time interaction. Based on this, we propose behavior recognition system for user's behavior recognition and service to observers in collaborative environment. Based on the proposed system, it solves the problem of servers overload due to large sensor data and the inability of real time interaction due to non-proximity between users and servers. This shows the process of delivering behavior recognition services that are consistent and capable of real time interaction.

• Spatial Information Research
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• v.20 no.1
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• pp.59-69
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• 2012

For the USN(Ubiquitous Sensor Network) environment which generally uses spatial sensor data as well as aspatial sensor data, a sensor database system to manage these sensor data is essential. In this reason, some sensor database systems such as TinyDB, Cougar are being developed by many researchers. However, since most of them do not support spatial data types and spatial operators to manage spatial sensor data, they have difficulty in processing spatial sensor data. Therefore, this paper developed a spatial sensor database system by extending TinyDB. Especially, the system supports spatial data types and spatial operators to TinyDB in order to manage spatial sensor data efficiently and provides the memory management function and the filtering function to reduce the system overload caused by sensor data streams. Lastly, we compared the processing time, accuracy, and memory usage of the spatial sensor database system with those of TinyDB and proved its superiority through the performance evaluation.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.91.4-91
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• 2001

In this paper, a development of the sensor fusion algorithm for a visual control of mobile robot is presented. The output data from the visual sensor include a time-lag due to the image processing computation. The sampling rate of the visual sensor is considerably low so that it should be used with other sensors to control fast motion. The main purpose of this paper is to develop a method which constitutes a sensor fusion system to give the optimal state estimates. The proposed sensor fusion system combines the visual sensor and inertial sensor using a modified Kalman filter. A kind of multi-rate Kalman filter which treats the slow sampling rate ...