• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.10
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• pp.4799-4804
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• 2013

Green IT technology for the growth of low-carbon green environment and future development of the new technology. Therefore, in this paper, data generated by the security module for RFID applications, smart green building Sung multi-function sensor integrated module that can be integrated environment for building monitoring and management system has been developed. The development of a thermal sensor, temperature sensor, smog sensor, CO2 sensor, O2 sensor, tension sensor and damage detection sensor module with integrated system module integrated multi-functional sensors implemented in the paper. In real-time monitoring by allowing was design and developed system that can be implemented smart green building environment for the environment inside buildings.

• International Journal of Control, Automation, and Systems
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• v.1 no.4
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• pp.444-452
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• 2003

An integration system with multi-measurement sets can be realized via combined application of a centralized and federated Kalman filter. It is difficult for the centralized Kalman filter to remove a failed sensor in comparison with the federated Kalman filter. All varieties of Kalman filters monitor innovation sequence (residual) for detection and isolation of a failed sensor. The innovation sequence, which is selected as an indicator of real time estimation error plays an important role in adaptive mechanism design. In this study, the centralized Kalman filter with adaptive measurement fusion is introduced by means of innovation sequence. The objectives of adaptive measurement fusion are automatic isolation and recovery of some sensor failures as well as inherent monitoring capability. The proposed adaptive filter is applied to the GPS/SDINS integration system with an additional sensor. Simulation studies attest that the proposed adaptive scheme is effective for isolation and recovery of immediate sensor failures.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.627-630
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• 2009

The combination of the marine use various multi sensor surveillance system technology with the development of servo motion control algorithm and gyro sensor in six freedom motion is implemented to analyze the movement response. The stabilization of the motion control is developed and Nano driving Precision Pan-Tilt/Gimbal system is obtained from the security positioning cameras with ultra high speed device is used to carry out the exact behavior of the device. The exact behavior will be used to make a essential equipment. Finally the development of the Nano Driving Multi Sensor, Nano of Surveillance System Driving Precision Pan-Tilt/Gimbal optimal design and production, 3-aix Gyro Sensor based with Servo Motion Control algorithm development, Image trace video software and hardware tracking the development is organized and discuss in details. The development of the equipment and the system integration are fully experimented and verified.

• KIISE Transactions on Computing Practices
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• v.23 no.2
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• pp.104-109
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• 2017

We propose a new machine learning algorithm which analyzes daily activity patterns of users from multi-modal wearable sensor data. The proposed model learns and extracts activity patterns using input from wearable devices in real-time. Inspired by cue integration of human's property, we constructed gated multi-modal neural networks which integrate wearable sensor input data selectively by using gate modules. For the experiments, sensory data were collected by using multiple wearable devices in restaurant situations. As an experimental result, we first show that the proposed model performs well in terms of prediction accuracy. Then, the possibility to construct a knowledge schema automatically by analyzing the activation patterns in the middle layer of our proposed model is explained.

• ETRI Journal
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• v.29 no.4
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• pp.411-420
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• 2007

The steady evolution of mapping technology is leading to an increasing availability of multi-sensory geo-spatial datasets, such as data acquired by single-head frame cameras, multi-head frame cameras, line cameras, and light detection and ranging systems, at a reasonable cost. The complementary nature of the data collected by these systems makes their integration to obtain a complete description of the object space. However, such integration is only possible after accurate co-registration of the collected data to a common reference frame. The registration can be carried out reliably through a triangulation procedure which considers the characteristics of the involved data. This paper introduces algorithms for a multi-primitive and multi-sensory triangulation environment, which is geared towards taking advantage of the complementary characteristics of spatial data available from the above mentioned sensors. The triangulation procedure ensures the alignment of involved data to a common reference frame. The devised methodologies are tested and proven efficient through experiments using real multi-sensory data.

• Journal of Sensor Science and Technology
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• v.3 no.1
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• pp.54-60
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• 1994

In this paper, the multi-sensor signal processing IC is designed. It consists of an analog multiplexer for selection of multi-sensor signals, active filters for noise rejection and signal amplification, and a sample and hold circuit for interface with digital signal processing. By implementing these circuits with CMOS transistors, integration, low power dissipation and miniaturization of the total signal processing system have been made possible.

• Journal of Astronomy and Space Sciences
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• v.20 no.4
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• pp.359-364
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• 2003

In this paper, we present multi-sensor data fusion for telematics application. Successful telematics can be realized through the integration of navigation and spatial information. The well-determined acquisition of vehicle's position plays a vital role in application service. The development of GPS is used to provide the navigation data, but the performance is limited in areas where poor satellite visibility environment exists. Hence, multi-sensor fusion including IMU (Inertial Measurement Unit), GPS(Global Positioning System), and DMI (Distance Measurement Indicator) is required to provide the vehicle's position to service provider and driver behind the wheel. The multi-sensor fusion is implemented via algorithm based on Kalman filtering technique. Navigation accuracy can be enhanced using this filtering approach. For the verification of fusion approach, land vehicle test was performed and the results were discussed. Results showed that the horizontal position errors were suppressed around 1 meter level accuracy under simulated non-GPS availability environment. Under normal GPS environment, the horizontal position errors were under 40㎝ in curve trajectory and 27㎝ in linear trajectory, which are definitely depending on vehicular dynamics.

• Proceedings of the Korea Contents Association Conference
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• 2014.06a
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• pp.435-436
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• 2014

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.23.3-23
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• 2001

The main object of this work is the development of an intelligent multi-sensor integration and fusion model that uses fuzzy inference system. Sensor data from different types of sensors are integrated and fused together based on the confidence which is not typically used in traditional data fusion methods. The information is fed as input to a fuzzy inference system(FIS). The output of the FIS is weights that are assigned to the different sensor data reflecting the confidence En the sensor´s behavior and performance. We interpret a type of fuzzy inference system as an interpolator of B-spline hypersurfaces. B-spline basis functions of different orders are regarded as a class of membership functions. This paper presents a model that ...

• Journal of Sensor Science and Technology
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• v.19 no.6
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• pp.475-482
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• 2010

Rogowski coil which detects magnetic flux on current changes. It is used for digital integration with watt-hour meter's current sensor, because, Rogowski coil has non-cored or non-magnetic core structure, so that, it cannot be saturated magnetically. This is a study for inventing accurate electric current sensors that have been applied on multi-layer ceramic substrate. We have confirmed its properties from each different layer's materials and pattern sizes by MWS 3D Electromagnetic field analysis program. And, after sensor manufacturing on multi-layer ceramic substrate, we confirmed its sensing quality is reliable as accurate electric current sensor for watt-hour meter.