• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.725-727
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• 2010

For simulation of Boat motion, pitch, motion element of roll and yaw direction could simulated. 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.6
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• pp.597-611
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• 2009

With the advent of ubiquitous computing society, many advanced technologies have enabled wireless sensor networks which consist of small sensor nodes. However, the sensor nodes have limited computing resources such as small size memory, low battery life, short transmission range, and low computational capabilities. Thus, decreasing energy consumption is one of the most significant issues in wireless sensor networks. In addition, numerous applications for wireless sensor networks are recently spreading to various fields (health-care, surveillance, location tracking, unmanned monitoring, nuclear reactor control, crop harvesting control, u-city, building automation etc.). For many of them, supporting security functionalities is an indispensable feature. Especially in case wireless sensor networks should provide a sufficient variety of security functions, sensor nodes are required to have more powerful performance and more energy demanding features. In other words, simultaneously providing security features and saving energy faces a trade-off problem. This paper presents a novel energy-efficient security architecture in an IEEE 802.15.4-based wireless sensor network called the Hybrid Adaptive Security (HAS) framework in order to resolve the trade off issue between security and energy. Moreover, we present a performance analysis based on the experimental results and a real implementation model in order to verify the proposed approach.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2006.07a
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• pp.367-367
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• 2006

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.3
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• pp.901-920
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• 2015

Wireless Sensor Networks (WSNs) are widely used in geographically isolated applications like military border area monitoring, battle field surveillance, forest fire detection systems, etc. Uninterrupted power supply is not possible in isolated locations and hence sensor nodes live on their own battery power. Localization of sensor nodes in isolated locations is important to identify the location of event for further actions. Existing localization algorithms consume more energy at sensor nodes for computation and communication thereby reduce the lifetime of entire WSNs. Existing approaches also suffer with less localization coverage and localization accuracy. The objective of the proposed work is to increase the lifetime of WSNs while increasing the localization coverage and localization accuracy. A novel intelligent unmanned aerial vehicle anchor node (IUAN) is proposed to reduce the communication cost at sensor nodes during localization. Further, the localization computation cost is reduced at each sensor node by the proposed intelligent arc selection (IAS) algorithm. IUANs construct the location-distance messages (LDMs) for sensor nodes deployed in isolated locations and reach the Control Station (CS). Further, the CS aggregates the LDMs from different IUANs and computes the position of sensor nodes using IAS algorithm. The life time of WSN is analyzed in this paper to prove the efficiency of the proposed localization approach. The proposed localization approach considerably extends the lifetime of WSNs, localization coverage and localization accuracy in isolated environments.

• Journal of Communications and Networks
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• v.11 no.1
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• pp.57-71
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• 2009

Networking together hundreds or thousands of cheap sensor nodes allows users to accurately monitor a remote environment by intelligently combining the data from the individual nodes. As sensor nodes are typically battery operated, it is important to efficiently use the limited energy of the nodes to extend the lifetime of the wireless sensor network (WSN). One of the fundamental issues in WSNs is the coverage problem. In this paper, the border coverage problem in WSNs is rigorously analyzed. Most existing results related to the coverage problem in wireless sensor networks focused on planar networks; however, three dimensional (3D) modeling of the sensor network would reflect more accurately real-life situations. Unlike previous works in this area, we provide distributed algorithms that allow the selection and activation of an optimal border cover for both 2D and 3D regions of interest. We also provide self-healing algorithms as an optimization to our border coverage algorithms which allow the sensor network to adaptively reconfigure and repair itself in order to improve its own performance. Border coverage is crucial for optimizing sensor placement for intrusion detection and a number of other practical applications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.11
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• pp.5476-5496
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• 2016

Energy efficiency of resource-constrained wireless sensor networks is critical in applications such as real-time monitoring/surveillance. To improve the energy efficiency and reduce the energy consumption, the time series data can be compressed before transmission. However, most of the compression algorithms for time series data were developed only for single variate scenarios, while in practice there are often multiple sensor nodes in one application and the collected data is actually multivariate time series. In this paper, we propose to compress the time series data by the Lasso (least absolute shrinkage and selection operator) approximation. We show that, our approach can be naturally extended for compressing the multivariate time series data. Our extension is novel since it constructs an optimal projection of the original multivariates where the best energy efficiency can be realized. The two algorithms are named by ULasso (Univariate Lasso) and MLasso (Multivariate Lasso), for which we also provide practical guidance for parameter selection. Finally, empirically evaluation is implemented with several publicly available real-world data sets from different application domains. We quantify the algorithm performance by measuring the approximation error, compression ratio, and computation complexity. The results show that ULasso and MLasso are superior to or at least equivalent to compression performance of LTC and PLAMlis. Particularly, MLasso can significantly reduce the smooth multivariate time series data, without breaking the major trends and important changes of the sensor network system.

• Journal of the Korea Society of Computer and Information
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• v.20 no.6
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• pp.87-97
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• 2015

An Aerial video summarization is not only the key to effective browsing video within a limited time, but also an embedded cue to efficiently congregative situation awareness acquired by unmanned aerial vehicle. Different with previous works, we utilize sensor operation mode of unmanned aerial vehicle, which is global, local, and focused surveillance mode in order for accurately summarizing the aerial video considering flight and surveillance/reconnaissance environments. In focused mode, we propose the moving-react tracking method which utilizes the partitioning motion vector and spatiotemporal saliency map to detect and track the interest moving object continuously. In our simulation result, the key frames are correctly detected for aerial video summarization according to the sensor operation mode of aerial vehicle and finally, we verify the efficiency of video summarization using the proposed mothed.

• Atmosphere
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• v.20 no.2
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• pp.153-160
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• 2010

In this paper, an attempt has been made to build and test self-configuring weather sensor networks and internet based observation system to gather atmospheric data. The aim is to provide integrated or real-time weather information in standard form using network data access protocol. This system was successfully developed to record weather information both digital as well as visual using sensor network and web-enabled surveillance cameras. These data were transformed by network based data access protocol to access and utilize for public domain. The competed system has been successfully utilized to monitor different types of weather. The results show that this is one of the most useful weather monitoring system.

• Journal of the Korea Institute of Military Science and Technology
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• v.9 no.2 s.25
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• pp.20-25
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• 2006

Low frequency towed line array with high array gain and beam resolution is a long range surveillance sensor for anti-submarine warfare. The beam characteristics is however deteriorated due to the distorted line array sensor caused by low towing speed, wind, current, and towing ship maneuvering. An adaptive beamforming method is utilized in this paper to enhance the distorted line array beam performance by estimating and compensating the nonlinear array shape. A polynomial curve fitting in the least square sense is used to estimate the array shape iteratively with the distributed heading sensors data along the array. Real time array shape estimation and nonlinear array beam calculation is applied to a very long towed line array sensor system and the beam performance is evaluated and compared to the linear beamformer for the simulation and sea trial data.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.2
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• pp.205-210
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• 2017

Wireless sensor networks are useful to various unmanned monitoring application such as monitoring environments, surveillance system, unmanned space exploration, and so on. Due to the inappropriate placement of sensor nodes, there are some problems, for example, low connectivity and high overlapped sensing area. These problems can make it difficult for the data collection and lead to a waste of energy. In this paper, we propose a node relocating method to resolve the inappropriate placement of sensor nodes. Given monitoring area, we place sensor nodes randomly and find redundant nodes and move them to uncovered area. Through the simulation, We show that the proposed method is viable and efficient compared with the existing randomly locating method.