• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.9
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• pp.1082-1087
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• 2019

Video Incident Detection System is a detection system for the purpose of detection of an emergency in an unexpected situation such as a pedestrian in a tunnel, a falling object, a stationary vehicle, a reverse run, and a fire(smoke and flame). In recent years, the importance of the city center has been emphasized by the construction of underpasses in great depth underground space. Therefore, in order to apply Video Incident Detection System to a Double Deck Tunnel, it was developed to reflect the design characteristics of the Double Deck Tunnel. and In this paper especially, the fire detection technology, which is not it is difficult to apply to the Double Deck Tunnel environment because it is not supported on existing Video Incident Detection System or has a fail detect, we propose fire detection using color image analysis, silhouette spread, and statistical properties, It is verified through a real fire test in a double deck tunnel test bed environment.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.6
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• pp.289-296
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• 2018

Drone detection in FMCW radar system needs complex techniques because a drone beat frequency is highly dynamic and unpredictable. Therefore, the current static signal processing algorithms cannot show appropriate detection accuracy. With dynamic signal fluctuation and environmental clutters, it can fail to detect a drone or make false detection. It affects to the radar system integrity and safety. Constant false alarm rate (CFAR), one of famous static signal process algorithm is effective for static environment. But for drone detection, it shows low detection accuracy. In this paper, we suggest neural network based FMCW radar system for detecting a drone. We use recurrent neural network (RNN) because it is the effective neural network for signal processing. In our FMCW radar system, one transmitter emits FMCW signal and four-way fixed receivers detect reflected drone beat frequency. The coordinate of the drone can be calculated with four receivers information by triangulation. Therefore, RNN only learns and inferences reflected drone beat frequency. It helps higher learning and detection accuracy. With several drone flight experiments, RNN shows false detection rate and detection accuracy as 21.1% and 96.4%, respectively.

• Journal of Digital Contents Society
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• v.19 no.4
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• pp.711-717
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• 2018

The breakthrough in computer and network has facilitated a variety of information exchange. However, at the same time, malicious users and groups are attacking vulnerable systems. Intrusion Detection System(IDS) detects malicious behaviors through network packet analysis. However, it has a burden of processing a large amount of packets in a short time. Therefore, in order to solve these problem, we propose a network intrusion detection system that operates at kernel level to improve detection performance at user level. In fact, we confirmed that the network intrusion detection system implemented at kernel level improves packet analysis and detection performance.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.8
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• pp.719-724
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• 2012

A traffic detection system is a device that collects traffic information around an intersection. Most existing traffic detection systems provide very limited traffic information for signal control due to the restriction of vehicle detection area. A signal control scheme determines the transition among signal phases and the time that a phase lasts for. However, the existing signal control scheme do not resolve the traffic congestion effectively since they use restricted traffic information. In this paper, a new traffic detection system with a zone division signal control scheme is proposed to provide correct and detail traffic information and decrease the vehicle's waiting time at the intersection. The traffic detection system obtains traffic information in a way of vehicle-to-roadside communication between vehicles and sensor network. A new signal control scheme is built to exploit the sufficient traffic information provided by the proposed traffic detection system efficiently. Simulation results show that the proposed signal control scheme has 121 % and 56 % lower waiting time and delay time of vehicles at an intersection than other fuzzy signal control scheme.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.03a
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• pp.307-313
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• 1999

This paper reviews and assesses the analogy between the human immune system and network intrusion detection systems. The promising results from a growing number of proposed computer immune models for intrusion detection motivate this work. The paper begins by briefly introducing existing intrusion detection systems (IDS's). A set of general requirements for network-based IDS's and the design goals to satisfy these requirements are identified by a careful examination of the literature. An overview of the human immune system is presented and its salient features that can contribute to the design of competent network-based IDS's are analysed. The analysis shows that the coordinated actions of several sophisticated mechanisms of the human immune system satisfy all the identified design goals. Consequently, the paper concludes that the design of a network-based IDS based on the human immune system is promising for future network-based IDS's

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.8
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• pp.734-741
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• 2004

This paper presents a network based fire detection system using CAN, in order to evaluate feasibility of home automation protocol for smart home. In general, because a traditional fire detection system has an analog transmission method with 4-20mA current, it has several shortcomings such as weakness to noise. Hence, as an alternative to the traditional system, this paper presents the architecture of CAN based fire detection system and the design method of CAN communication network. Also, the performance of the suggested system is evaluated through an experimental testbed. Especially, CAN has several advantages such as low cost and easiness of implementation compared to Ethernet or ARCNET, which are low layer of BACNet. Therefore, if CAN is adopted as low layer of BACNet, the home automation system is implemented more effectively.

• Journal of Ocean Engineering and Technology
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• v.8 no.1
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• pp.62-70
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• 1994

In order to estimate the detection range of a active SONAR system, the SONAR equation is commonly used. In this paper, an algorithm to calculate detection range in active SONAR system as function of SONAR depth and target depth is presented. For given SONAR parameters and environment, the transmission loss and background level are found, signal excess is computed. Using log-normal distribution, signal excess is converted to detection probability at each range. Then, the detection range is obtained by integrating the detection probability as function of range for each depth. The proposed algorithm have been applied to the case of omni-directional source with center frequency 30Hz for summer and winter sound profiles. It is found that the optimal search depth is the source depth since the detection range increase at source depth where the signal excess is maximized.

• Journal of the Semiconductor & Display Technology
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• v.20 no.3
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• pp.125-130
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• 2021

Scaffold is used to produce bio sensor. Scaffold is required high dimensional accuracy. 3D printer is used to manufacture scaffold. 3D printer can't detect defect during printing. Defect detection is very important in scaffold printing. Real-time defect detection is very necessary on industry. In this paper, we proposed the method for real-time scaffold defect detection. Real-time defect detection model is produced using CNN(Convolution Neural Network) algorithm. Performance of the proposed model has been verified through evaluation. Real-time defect detection system are manufactured on hardware. Experiments were conducted to detect scaffold defects in real-time. As result of verification, the defect detection system detected scaffold defect well in real-time.

• Journal of Multimedia Information System
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• v.6 no.4
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• pp.329-332
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• 2019

Recently, smart lighting systems are the combination between sensors and lights. These systems turn on/off and adjust the brightness of lights based on the motion of object and the brightness of environment. These systems are often applied in places such as buildings, rooms, garages and parking lot. However, these lighting systems are controlled by lighting sensors, motion sensors based on illumination environment and motion detection. In this paper, we propose an automatic lighting control system using one single camera for buildings, rooms and garages. The proposed system is one integration the results of digital image processing as motion detection, hand gesture detection to control and dim the lighting system. The experimental results showed that the proposed system work very well and could consider to apply for automatic lighting spaces.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.315-318
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• 2015

in recently the world trend of security system for shipping transport is much more important and stronger, so following the world trend, there is development to security system of shipping transport for national security logistics system construction. it is still ongoing. For the world trend of security system, there is attempt of portable radiation detection, which is possible to get detection of nuclide in south Korea. in this Paper, it will shows about Full-digital system to portable radiation detection platform.