• IEMEK Journal of Embedded Systems and Applications
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• v.7 no.5
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• pp.209-217
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• 2012

In the present, Wireless Sensor Network(WSN) has been used for the purpose of the military operation with surveillance systems and for collecting useful information from the natural environment. Basically, low-power, easy deployment and low cost are the most important factors to be deployed for WSNs. Lots of researches have been studied to meet those requirements, especially on the node capacity and battery lifetime improvements. Recently, the study of wireless mesh networks applied into the surveillance systems has been proceeded as a solution of easy deployment. In this paper, we proposed large-scale intelligent multi-layer surveillance systems based on QoS assuring Wireless Mesh Networks and implemented them in the real testbed environment. The proposed system explains functions and operations for each subsystem as well as S/W and H/W architectures. Experimental results are shown for the implemented subsystems and the performance is satisfactory for the surveillance system. We can identify the possibility of the implemented multi-layer surveillance system to be used in practice.

• Journal of the Korean Society of Systems Engineering
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• v.15 no.1
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• pp.16-24
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• 2019

In this study, an improved method of setting the RAM goals for surveillance system using OMS/MP and field operations data of similar systems is suggested and a case study of surveillance system A is given. Newly suggested methods for setting the RAM goals consist of the procedures such as On/Off time analysis of configuration equipment based on OMS/MP, field operations data analysis of similar systems, adjustment of preventive maintenance time, the number of corrective maintenances, and TALDT in wartime, introducing new subsystem to reliability structure of surveillance system, and reflecting expert's opinion. A case study of surveillance system A shows that newly suggested method in this study for setting the RAM goals is reasonably acceptable and practically applicable to other similar systems.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.11
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• pp.989-995
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• 2015

Due to the recent increase of the importance and demand of security services, the importance of a surveillance monitor system that makes an automatic security system possible is increasing. As the market for surveillance monitor systems is growing, price competitiveness is becoming important. As a result of this trend, surveillance monitor systems based on an embedded system are widely used. In this paper, an object detection algorithm based on an embedded system for a surveillance monitor system is introduced. To apply the object detection algorithm to the embedded system, the most important issue is the efficient use of resources, such as memory and processors. Therefore, designing an appropriate algorithm considering the limit of resources is required. The proposed algorithm uses two background models; therefore, the embedded system is designed to have two independent processors. One processor checks the sub-background models for if there are any changes with high update frequency, and another processor makes the main background model, which is used for object detection. In this way, a background model will be made with images that have no objects to detect and improve the object detection performance. The object detection algorithm utilizes one-dimensional histogram distribution, which makes the detection faster. The proposed object detection algorithm works fast and accurately even in a low-priced embedded system.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2003.11a
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• pp.135-144
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• 2003

In this paper, the implementation techniques of intelligent nuclear material surveillance system based on the SOM(Self Organized Mapping) was described. Unattended continuous surveillance systems for nuclear facility result in large amounts of data, which require much time and effort to inspect. Therefore, it is necessary to develop system that automatically pinpoints and diagnoses the anomalies from data. In this regards, this paper presents a novel concept of a continuous surveillance system that integrates visual image and radiation data by the use of neural networks based on self-organized feature mapping

• Journal of Advanced Navigation Technology
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• v.20 no.3
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• pp.203-209
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• 2016

Among the various fields in the communications, navigation, and surveillance/air traffic management (CNS/ATM) scheme, the surveillance field, which includes an automatic dependent surveillance - broadcast (ADS-B) system and a multilateration (MLAT) system, is implemented using satellite and digital communications technology. These systems provide better performance than radar, but still incur position error. To reduce the error, we propose an efficient information fusion method called the reweighted convex combination method for ADS-B and MLAT systems. The reweighted convex combination method improves aircraft tracking performance compared to the original convex combination method by readjusting the weights given to these systems. In this paper, we prove that the reweighted convex combination method always provides better performance than the original convex combination method. Performance from the fusion of ADS-B and MLAT improves an average of 51.51% when compared to the original data.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.2
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• pp.138-146
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• 2012

Using Shear-free Ship wake theory it was predicted the detectable submarine's turbulent wake on the sea surface was about 12km long when there was no breaking waves on the sea surface. It means that there are sufficient detectable turbulent kinetic energies on the sea surface as well as in the water. In this paper, we have proposed some concepts of non acoustic anti-submarine surveillance systems; SAR for sea surface surveillance, LIDAR for sub-surface surveillance and propelled gliders for under -water surveillance.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.11
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• pp.1559-1563
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• 2014

Recently, the prevention of crime using CCTV draws special in accordance with the higher crime incidence rate. Therefore security systems like a CCTV with audio capability are developing for giving an instant alarm. This paper proposes a scream detecting engine from various ambient noises in real environment for surveillance systems. The proposed engine detects scream signals among the various ambient noises using the features extracted in time/frequency domain. The experimental result shows the performance of our engine is very promising in comparison with the traditional engines using the model based features like LPC, LPCC and MFCC. The proposed method has a low computational complexity by using FFT and cross correlation coefficients instead of extracting complex features like LPC, LPCC and MFCC. Therefore the proposed engine can be efficient for audio-based surveillance systems with low SNRs in real field.

• Journal of the Semiconductor & Display Technology
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• v.14 no.3
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• pp.37-43
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• 2015

In this paper, a new background subtraction algorithm for video based fence monitoring surveillance systems is proposed. We adopt the sampling based background subtraction technique and focus on the two main issues: handling highly dynamic environment and handling the flickering nature of pulse based IR (infrared) lamp. Natural scenes from fence monitoring system are usually composed of several dynamic entities such as swaying trees, moving water, waves and rain. To deal with such dynamic backgrounds, we utilize the confidence factor for each background value of the input image. For the flickering IR lamp, the original sampling based technique is extended to handle double background models. Experimental results revealed that our method works well in real fence monitoring surveillance systems.

• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.2
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• pp.71-77
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• 2017

This paper proposes a low complexity frequency modulated continuous wave (FMCW) surveillance radar algorithm. In the conventional surveillance radar systems, the two dimensional (2D) fast Fourier transform (FFT) method is usually employed in order to detect the distance and velocity of the targets. However, in a surveillance radar systems, it is more important to immediately detect the presence or absence of the targets, rather than accurately detecting the distance or speed information of the target. In the proposed algorithm, in order to immediately detect the presence or absence of targets, 1D FFT is performed on the first and M-th bit signals among a total of M beat signals and then a phase change between two FFT outputs is observed. The range of target is estimated only when the phase change occurs. By doing so, the proposed algorithm achieves a significantly lower complexity compared to the conventional surveillance scheme using 2D FFT. In addition, show in order to verify the performance of the proposed algorithm, the simulation and the experiment results are performed using 24GHz FMCW radar module.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.8
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• pp.780-786
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• 2012

Surveillance has become one of promising application areas of wireless sensor networks which allow for pervasive monitoring of concerned environmental phenomena by facilitating context awareness through sensor fusion. Existing systems that depend on a postmortem context analysis of sensor data on a centralized server expose several shortcomings, including a single point of failure, wasteful energy consumption due to unnecessary data transfer as well as deficiency of scalability. As an opposite direction, this paper proposes an energy-efficient distributed context-aware surveillance in which sensor nodes in the wireless sensor network collaborate with neighbors in a distributed manner to analyze and aware surrounding context. We design and implement multi-modal sensor stations for use as sensor nodes in our wireless sensor network implementing our distributed context awareness. This paper presents an initial experimental performance result of our proposed system. Results show that multi-modal sensor performance of our sensor station, a key enabling factor for distributed context awareness, is comparable to each independent sensor setting. They also show that its initial performance of context-awareness is satisfactory for a set of introductory surveillance scenarios in the current interim stage of our ongoing research.