• Journal of Internet Computing and Services
• /
• v.15 no.3
• /
• pp.45-52
• /
• 2014

The Ubiquitous-City (U-City) is a smart or intelligent city to satisfy human beings' desire to enjoy IT services with any device, anytime, anywhere. It is a future city model based on Internet of everything or things (IoE or IoT). It includes a lot of video cameras which are networked together. The networked video cameras support a lot of U-City services as one of the main input data together with sensors. They generate huge amount of video information, real big data for the U-City all the time. It is usually required that the U-City manipulates the big data in real-time. And it is not easy at all. Also, many times, it is required that the accumulated video data are analyzed to detect an event or find a figure among them. It requires a lot of computational power and usually takes a lot of time. Currently we can find researches which try to reduce the processing time of the big video data. Cloud computing can be a good solution to address this matter. There are many cloud computing methodologies which can be used to address the matter. MapReduce is an interesting and attractive methodology for it. It has many advantages and is getting popularity in many areas. Video cameras evolve day by day so that the resolution improves sharply. It leads to the exponential growth of the produced data by the networked video cameras. We are coping with real big data when we have to deal with video image data which are produced by the good quality video cameras. A video surveillance system was not useful until we find the cloud computing. But it is now being widely spread in U-Cities since we find some useful methodologies. Video data are unstructured data thus it is not easy to find a good research result of analyzing the data with MapReduce. This paper presents an analyzing system for the video surveillance system, which is a cloud-computing based video data management system. It is easy to deploy, flexible and reliable. It consists of the video manager, the video monitors, the storage for the video images, the storage client and streaming IN component. The "video monitor" for the video images consists of "video translater" and "protocol manager". The "storage" contains MapReduce analyzer. All components were designed according to the functional requirement of video surveillance system. The "streaming IN" component receives the video data from the networked video cameras and delivers them to the "storage client". It also manages the bottleneck of the network to smooth the data stream. The "storage client" receives the video data from the "streaming IN" component and stores them to the storage. It also helps other components to access the storage. The "video monitor" component transfers the video data by smoothly streaming and manages the protocol. The "video translator" sub-component enables users to manage the resolution, the codec and the frame rate of the video image. The "protocol" sub-component manages the Real Time Streaming Protocol (RTSP) and Real Time Messaging Protocol (RTMP). We use Hadoop Distributed File System(HDFS) for the storage of cloud computing. Hadoop stores the data in HDFS and provides the platform that can process data with simple MapReduce programming model. We suggest our own methodology to analyze the video images using MapReduce in this paper. That is, the workflow of video analysis is presented and detailed explanation is given in this paper. The performance evaluation was experiment and we found that our proposed system worked well. The performance evaluation results are presented in this paper with analysis. With our cluster system, we used compressed $1920{\times}1080(FHD)$ resolution video data, H.264 codec and HDFS as video storage. We measured the processing time according to the number of frame per mapper. Tracing the optimal splitting size of input data and the processing time according to the number of node, we found the linearity of the system performance.

• Journal of the Korean Society for Marine Environment & Energy
• /
• v.16 no.1
• /
• pp.1-8
• /
• 2013

This study focuses on a ship detection and tracking method using Frequency Modulated Continuous Wave (FMCW) radar used for horizontal surveillance. In general, FMCW radar can play an important role in maritime surveillance, because it has many advantages such as low warm-up time, low power consumption, and its all weather performance. In this paper, we introduce an effective method for data and signal processing of ship's detecting and tracking using the X-band radar. Ships information was extracted using an image-based processing method such as the land masking and morphological filtering with a threshold for a cycle data merged from raw data (spoke data). After that, ships was tracked using search-window that is ship's expected rectangle area in the next frame considering expected maximum speed (19 kts) and interval time (5 sec). By using this method, the tracking results for most of the moving object tracking was successful and those results were compared with AIS (Automatic Identification System) for ships position. Therefore, it can be said that the practical application of this detection and tracking method using FMCW radar improve the maritime safety as well as expand the surveillance coverage cost-effectively. Algorithm improvements are required for an enhancement of small ship detection and tracking technique in the future.

• KIPS Transactions on Software and Data Engineering
• /
• v.7 no.3
• /
• pp.99-106
• /
• 2018

In the process of acquiring information through the cyber ISR (Intelligence Surveillance Reconnaissance) and research into the agent to help decision-making, periodic communication between the C&C (Command and Control) server and the agent may not be possible. In this case, we have studied how to effectively surveillance and reconnaissance. Due to the network configuration, agents planted on infiltrated computers can not communicate seamlessly with C&C servers. In this case, the agent continues to collect data continuously, and in order to analyze the collected data within a short time in When communication is possible with the C&C server, it can utilize limited resources and time to continue its mission without being discovered. This research shows the superiority of incremental learning method over batch method through experiments. At an experiment with the restricted memory of 500 mega bytes, incremental learning method shows 10 times decrease in learning time. But at an experiment with the reuse of incorrectly classified data, the required time for relearn takes twice more.

• The KIPS Transactions:PartC
• /
• v.19C no.3
• /
• pp.209-214
• /
• 2012

Time synchronization is important role in a network, especially in Wireless Sensor Network (WSN) which is required for time-critical applications such as surveillance, tracking, data fusion and scheduling. Time synchronization in WSN should meet the other different requirements than the one in other networks because WSN has critical resource constraints, especially power consumption. This paper presents a new time synchronization scheme for WSN, which is energy efficient by reducing communication overhead. Simulation test shows this new scheme has better energy efficiency and performance of accuracy than existing schemes proposed previously.

• Proceedings of the IEEK Conference
• /
• 2004.08c
• /
• pp.532-535
• /
• 2004

Architecture generation is the first step in the design of software systems. Most of the qualities that the final software system possesses are usually decided at the architecture development stage itself. Thus, if the final system should be usable, testable, secure, high performance, mobile and adaptable, then these qualities or non­functional requirements should be engineered into the architecture itself. In particular, adaptability is emerging as an important attribute required by almost all software systems. The machinery and tools in the remote site surveillance and connects intelligence information machinery and tools at Internet. We need the server which uses different embedded operating system to become private use. With the progress of information-oriented society, many device with advanced technologies invented by many companies. However, the current firmware technologies have many problems to meet such high level of new technologies. In this paper, we have successfully ported linux on an embedded system, which is based on intel StrongARM SA-1 1 10 processor, then written several network modules for internet-based network devices.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.12 no.5
• /
• pp.319-330
• /
• 2017

In remote USV (Unmanned Surface Vehicle) maritime operation, the remote operation and control technic and autonomous control technic is required and the emergency mode algorithm is needed certainly for sailing and accomplishing various surveillance, reconnaissance, and underwater search missions of USV. In this paper, we review the countermeasures in emergency situation of the existing USV system (Barracuda) and propose the emergency mode algorithm considering the operation and control, and autonomous control level for the stable USV operation in case of emergency. We analyzed the autonomous control level in view of the mission complexity and environmental difficulty, and human interface, and verified the performance of the autonomous control level when we apply four emergency mode algorithms. It is expected that more stable and reliable operation and cotrol are possible if the proposed algorithm is applied to the environments requiring the various multi-mission USV sailing and mission achievement.

• Asian-Australasian Journal of Animal Sciences
• /
• v.26 no.7
• /
• pp.1030-1037
• /
• 2013

Early detection of anomalies is an important issue in the management of group-housed livestock. In particular, failure to detect oestrus in a timely and accurate way can become a limiting factor in achieving efficient reproductive performance. Although a rich variety of methods has been introduced for the detection of oestrus, a more accurate and practical method is still required. In this paper, we propose an efficient data mining solution for the detection of oestrus, using the sound data of Korean native cows (Bos taurus coreanea). In this method, we extracted the mel frequency cepstrum coefficients from sound data with a feature dimension reduction, and use the support vector data description as an early anomaly detector. Our experimental results show that this method can be used to detect oestrus both economically (even a cheap microphone) and accurately (over 94% accuracy), either as a standalone solution or to complement known methods.

• Proceedings of the KIEE Conference
• /
• 2008.10b
• /
• pp.268-269
• /
• 2008

Moving object detection is a fundamental technique in visual surveillance. Robust technique to enhance performance of moving object detection is required for several bad conditions in real external circumtance. In case of sudden illumination change in outdoor condition, many objects are determined as moving object though they are not really moving, but just their illumination changes. This makes the detection result untrustworthy. In this paper, robust moving object detection to sudden illumination change using gaussian mixture background model and new texture information using background from the weighted sum of recent images is proposed.

• Proceedings of the Korea Contents Association Conference
• /
• 2005.11a
• /
• pp.580-584
• /
• 2005

One of the problems of panoramic image stitching methods is that its computational cost is so high that the image processing required usually cannot be done in real-time. Real-time performance is important in applications such as video surveillance becausewe must see current scenes. But it takes more than several seconds to calculate transform coefficients between images. Panoramic VR technologies such as Apple QuickTime VR have problem that distorts images of top and bottom. This paper presents a fast stitching method and a methpd reducing distortions of top and bottom in cubic panoramic image.

• International Journal of Aeronautical and Space Sciences
• /
• v.16 no.4
• /
• pp.614-623
• /
• 2015

When the speed of a coaxial rotor helicopter in forward flight increases, the wake skew angle of the rotor increases and consequently the position of the vena contracta of the upper rotor with respect to the lower rotor changes. Considering ambient air and the effect of the upper rotor, this study proposes a nonuniform inflow model for the lower rotor of a coaxial rotor helicopter in forward flight. The total required power of the coaxial rotor system was compared against Dingeldein's experimental data, and the results of the proposed model were well matched. A plant model was also developed from first principles for flight simulation, unknown parameter estimation and control analysis. The coaxial rotor helicopter used for this study was manufactured for surveillance and reconnaissance and does not have any stabilizer bar. Therefore, a feedback controller was included during flight test and parameter estimation to overcome unstable situations. Predicted responses of parameter estimation and validation show good agreement with experimental data. Therefore, the methodology described in this paper can be used to develop numerical plant model, study non-uniform inflow model, conduct performance analysis and parameter estimation of coaxial rotor as well as other rotorcrafts in forward flight.