• Proceedings of the Korean Society of Computer Information Conference
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• 2014.07a
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• pp.109-110
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• 2014

본 연구에서는 공공 시설물 관리를 위한 센서 융합 기술을 활용한 M2M 기반의 외부 디바이스 및 내장 미들웨어 시스템을 개발하였다. 시설안전체계의 개선 및 M2M 기반기술을 접목한 기술개발을 통해 시설물 안전수준은 급격히 향상되고. 있다 무인 시설물 관리를 위하여 지속적인 촬영 및 저장방식이 아닌 센서와 영상 데이터를 융합하여 상황인지 방식의 외부 디바이스 및 내장 미들웨어 시스템을 개발하고 정보에 대한 신뢰성을 향상시켜 센서 융합형 외부 디바이스를 활용하여 이벤트 발생시에만 정보 전달을 통해 데이터 전송이 감소되는 효율적인 감시시스템을 개발하였다.

• Journal of Sensor Science and Technology
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• v.24 no.5
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• pp.348-352
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• 2015

Thin nickel oxide films formed on uncooled and cooled $SiO_2/Si$ substrates using a radio frequency (RF) magnetron sputter powered by 200 W in a mixed atmosphere of argon and oxygen. Grazing-incidence X-ray diffraction and field emission scanning electron microscopy are used for the structural analysis of nickel oxide films. The electrical conductivity required for better bolometric performance is estimated by means of a four-point probe system. Columnar and (200) preferred orientations are discovered in both films regardless of substrate cooling. Electric resistivity, however, is greatly influenced by the substrate cooling. Oxygen partial pressure increase during the nickel oxide deposition leads to a rapid decrease in resistivity, and the resistivity is higher in the cooled nickel oxide samples. Even when small microstructure variations are applied, lower resistivity in favor of low noise performance is acquired in the uncooled samples.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.7
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• pp.7-14
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• 2004

In an upcoming ubiquitous era, humankind will live in a ubiquitous space, where everything is connected through communication network. In this ubiquitous space, a ubiquitous robot, which can be used by anyone for any service through any device and any network at anytime and anywhere in a u-space, is expected to be required to serve seamless and context-aware services to humankind. In this paper, we introduce the ubiquitous robot, and define three components of the ubiquitous robot. The first one is "SoBot" which can be connected through the network in anywhere with environment recognition function and communication ability with human. The second one is "EmBot" which is embedded into environments and mobile robots and has localization and certification function with sensor fusion. The last one is "Mobile Robot" which serves overall physical services. This paper also introduces KAIST ITRC-Intelligent Robot Research Center that pursues the implementation of the ubiquitous robot.

• Journal of IKEEE
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• v.23 no.2
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• pp.710-715
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• 2019

We consider parameter estimation in distributed systems in which measurements at local nodes are quantized in a non-regular manner, where multiple codewords are mapped into a single local measurement. For the system with non-regular quantization, to ensure a perfect independent encoding at local nodes, a local measurement can be encoded into a set of a great number of codewords which are transmitted to a fusion node where estimation is conducted with enormous computational cost due to the large cardinality of the sets. In this paper, we propose an efficient estimation technique that can handle the non-regular quantized data by efficiently finding the feasible combination of codewords without searching all of the possible combinations. We conduct experiments to show that the proposed estimation performs well with respect to previous novel techniques with a reasonable complexity.

• Journal of Auto-vehicle Safety Association
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• v.14 no.3
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• pp.71-76
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• 2022

In autonomous driving cars, 3D pose estimation can be one of the effective methods to enhance safety control for OOP (Out of Position) passengers. There have been many studies on human pose estimation using a camera. Previous methods, however, have limitations in automotive applications. Due to unexplainable failures, CNN methods are unreliable, and other methods perform poorly. This paper proposes robust real-time multi-human 3D pose estimation architecture in vehicle using monocular RGB camera. Using particle filter, our approach integrates CNN 2D/3D pose measurements with available information in vehicle. Computer simulations were performed to confirm the accuracy and robustness of the proposed algorithm.

• Smart Structures and Systems
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• v.16 no.2
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• pp.295-328
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• 2015

In recent years the monitoring of structural behavior through acquisition of vibrational data has become common practice. In addition, recent advances in sensor development have made the collection of diverse dynamic information feasible. Other than the commonly collected acceleration information, Global Position System (GPS) receivers and non-contact, optical techniques have also allowed for the synchronous collection of highly accurate displacement data. The fusion of this heterogeneous information is crucial for the successful monitoring and control of structural systems especially when aiming at real-time estimation. This task is not a straightforward one as measurements are inevitably corrupted with some percentage of noise, often leading to imprecise estimation. Quite commonly, the presence of noise in acceleration signals results in drifting estimates of displacement states, as a result of numerical integration. In this study, a new approach based on a time domain identification method, namely the Unscented Kalman Filter (UKF), is proposed for correcting the "drift effect" in displacement or rotation estimates in an online manner, i.e., on the fly as data is attained. The method relies on the introduction of artificial white noise (WN) observations into the filter equations, which is shown to achieve an online correction of the drift issue, thus yielding highly accurate motion data. The proposed approach is demonstrated for two cases; firstly, the illustrative example of a single degree of freedom linear oscillator is examined, where availability of acceleration measurements is exclusively assumed. Secondly, a field inspired implementation is presented for the torsional identification of a tall tower structure, where acceleration measurements are obtained at a high sampling rate and non-collocated GPS displacement measurements are assumed available at a lower sampling rate. A multi-rate Kalman Filter is incorporated into the analysis in order to successfully fuse data sampled at different rates.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.4
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• pp.95-103
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• 2009

Global interests for construction of 3 dimensional spatial information has risen due to development of measurement sensors and data processing technologies. In spite of criticism for the violation of personal privacy, CCTV cameras equipped in outdoor public space of urban area are used as a fundamental sensor for traffic management, crime prevention or hazard monitoring. For safety guarantee in urban environment and disaster prevention, a surveillance system integrating pre-constructed 3 dimensional spatial information with CCTV data or video sequence is needed for monitoring and observing emergent situation interactively in real time. In this study, we proposed applicability of the prototype system for web visualization based on X3D, an international standard of real time web visualization, by integrating 3 dimensional spatial information with video sequence.

• International journal of advanced smart convergence
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• v.7 no.4
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• pp.50-56
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• 2018

The Internet of Things (IoT) and Visible Light Communication (VLC) is opening up new services in lighting industry by integrating sensory network features in addition to standard illumination functionality. In this progressive developments, the next generation lighting devices for smart homes are capable to sense the environmental conditions and transfer the captured data through lights to gateway controller to access remotely. The smart home environmental sensor information's are few kbps only so VLC systems need to built-in with low rate light connectivity to transfer data to the gateway. To provide error free communication, the quality of a received light signal is important to be considered when designing an VLC receiver. Therefore, this paper proposes the design of robust low rate IoL receiver design using NCP302 voltage detector for micro controller to adapt the IoT/IoL front end module for system integration. To evaluate the proposed system performance, the Arduino UNO based IoT/IoL controller designed with lighting, sensors and lights connectivity interfaces. The experimental result shows that the robust interference rejection is feasible on proposed VOL receiver and possible to have an error-free communication up to 10 kbps at a low SNR using OOK modulation.

• ETRI Journal
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• v.30 no.1
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• pp.59-67
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• 2008

The necessity for the precise time synchronization of measurement data from multiple sensors is widely recognized in the field of global positioning system/inertial navigation system (GPS/INS) integration. Having precise time synchronization is critical for achieving high data fusion performance. The limitations and advantages of various time synchronization scenarios and existing solutions are investigated in this paper. A criterion for evaluating synchronization accuracy requirements is derived on the basis of a comparison of the Kalman filter innovation series and the platform dynamics. An innovative time synchronization solution using a counter and two latching registers is proposed. The proposed solution has been implemented with off-the-shelf components and tested. The resolution and accuracy analysis shows that the proposed solution can achieve a time synchronization accuracy of 0.1 ms if INS can provide a hard-wired timing signal. A synchronization accuracy of 2 ms was achieved when the test system was used to synchronize a low-grade micro-electromechanical inertial measurement unit (IMU), which has only an RS-232 data output interface.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.6
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• pp.267-275
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• 2013

EKF has been widely used for GPS/INS integration as standard method but EKF has one well-known drawback. if the errors are not within the bounded region, the filter may be divergent. The particle filter has the advantage of the nonlinear and non-gaussian system. This paper proposes a method for compensating the GPS position errors based on the particle filter and presents loosely-coupled GPS/INS integration using proposed algorithm. We used GPS position pattern with particle filter and added attitude kalman filter for improving attitude accuracy. To verify the performance, the proposed method is compared with high cost GPS as reference. In the experimental result, we verified that the accuracy and robust were well improved by the proposed method filter effectively and robustness than by original loosely-coupled integration when vehicle turns at corner.