• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.7
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• pp.589-595
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• 2013

The agents for security surveillance are not enough for monitoring CCTV system, so the intelligent automatic surveillance system is needed. In this paper, object detection, tracking and abnormal event detection system is implemented for intelligent CCTV system. Each modules are tested on the real CCTV environment and promoted for commercialization. Abnormal event detection module and loitering detection and sudden running detection function and it's detection time is under 1 second which is satisfied level.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.11
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• pp.2115-2120
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• 2017

Presently, It is required to change convergence the role of hardware system and software technology that promoted trust of In-Vehicle for integrated complex system visibility evaluation. There is possibility for the period system can invoke unpredictable confusing blank state. The blank state systems have ecosystem characteristics that are supplied, maintained and operated through the complex interactions of technology and culture. Using universal middleware can support the life-cycle model and increase the visibility of complex systems and prepare for confusing situations. In this study, based on universal middleware, data and service dynamic standardized modules were evaluated to support stable system visibility platform. The system visibility module consists of Intelligent Pervasive Cloud module, Memorial Service module and Life Cycler connection module. In addition, the analysis results are supported by various network application service standards through platform independent system and architecture.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.2
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• pp.186-191
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• 2003

Skills in tracing of the MR divide into following, approaching, avoiding and warning and so on. It is difficult to have all these skills learned as neural network. To make this up for, skills consisted of each module, and Mobile Robot was controlled by the output of module adequate for the situation. A mobile Robot was equipped multi-ultrasonic sensor and a USB Camera, which can be in place of human sense, and the measured environment information data is learned through Modular Neural Network. MNN consisted of optimal combination of activation function in the Expert Network and its structure seemed to improve learning time and errors. The Gating Network(GN) used to control output values of the MNN by switching for angle and speed of the robot. In the paper, EN of Modular Neural network was designed optimal combination. Traveling with a real MR was performed repeatedly to verity the usefulness of the MNN which was proposed in this paper. The robot was properly controlled and driven by the result value and the experimental is rewarded with good fruits.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.4
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• pp.68-80
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• 2016

This study proposes the traffic prediction and optimal traffic control system based on cell transmission model and genetic algorithm in cloud environment. The proposed prediction and control system consists of four parts. 1) Data preprocessing module detects and imputes the corrupted data and missing data points. 2) Data-driven traffic prediction module predicts the future traffic state using Multi-level K-Nearest Neighbor (MK-NN) Algorithm with stored historical data in SQL database. 3) Online traffic simulation module simulates the future traffic state in various situations including accident, road work, and extreme weather condition with predicted traffic data by MK-NN. 4) Optimal road control module produces the control strategy for large road network with cell transmission model and genetic algorithm. The results show that proposed system can effectively reduce the Vehicle Hours Traveled upto 60%.

• The Transactions of the Korean Institute of Power Electronics
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• v.22 no.4
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• pp.360-368
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• 2017

This paper proposes the 80-kW high-efficiency bidirectional hybrid SiC boost/buck converter using droop control for DC nano-grid. The proposed converter consists of four 20-kW modules to achieve fault tolerance, ease of thermal management, and reduced component stress. Each module is constructed as a cascaded structure of the two basic bi-directional converters, namely, interleaved boost and buck converters. A six-pack hybrid SiC intelligent power module (IPM) suitable for the proposed cascaded structure is adopted for high-efficiency and compactness. The proposed converter with hybrid switching method reduces the switching loss by minimizing switching of insulated gate bipolar transistor (IGBT). Each module control achieves smooth transfer from buck to boost operation and vice versa, since current controller switchover is not necessary. Furthermore, the proposed parallel control using DC droop with secondary control, enhances the current sharing accuracy while well regulating the DC bus voltage. A 20-kW prototype of the proposed converter has been developed and verified with experiments and indicates a 99.3% maximum efficiency and 98.8% rated efficiency.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.6
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• pp.634-643
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• 1999

This paper concerns an implementation of f~rry logic controller (FLC') on a reconfigurahle FP

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.5
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• pp.718-723
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• 2007

In this paper, we developed a personal hypertension management system (PHMS) having self-diagnosis function with PDA. The developed PHMS consists of five modules such as a personal information management, a life management, a food management, a sickness management, and network management modules. The personal information management module offers physical and fatness information as well as personal information. The life management module gives exercise and body mass index. The food management module includes caloric intake and the sickness management module renders a personal blood pressure and a subjective symptom. Finally, wireless networks are implemented for the network management. From these, it is possible to make a self diagnosis and be examined and treated remotely by sending the stored blood pressure related information to a medical doctor.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.5
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• pp.64-76
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• 2008

To increase road safety at blackspots, it is needed to develop a new method that can process before accident occurrence. Accident situation could result from traffic conflict. Traffic conflict decision technique has an advantage that can acquire and analyze data in time and confined space that is less through investigation. Therefore, traffic conflict technique is highly expected to be used in many application of road safety. This study developed traffic conflict decision program that can analyze and process from signalized intersection image. Program consists of the following functional modules: an image input module that acquires images from the CCTV camera, a Save-to-Buffer module which stores the entered images by differentiating them into background images, current images, difference images, segmentation images, and a conflict detection module which displays the processed results. The program was developed using LabVIEW 8.5 (a graphic language) and the VISION module library.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.639-641
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• 2022

With the increasing of aging population, a lot of researches on monitoring systems for solitary senior citizens are under study. In general, a monitoring system provides a monitoring service by computing the information of vision, sensors, and measurement values on a server. Design considering data security is essential because a risk of data leakage exists in the structure of the system employing the server. In this paper, we propose a intelligent monitoring system for solitary senior citizens with vision-based security architecture. The proposed system protects privacy by ensuring high security through an architecture that blocks communication between a camera module and a server by employing an edge AI module. The edge AI module was designed with Verilog HDL and verified by implementing on a Field Programmable Gate Array (FPGA). We tested our proposed system on 5,144 frame data and demonstrated that a dangerous detection signal is generated correctly when human motion is not detected for a certain period.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1163-1168
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• 2005

This paper proposes a soft-remote-control (soft-remocon) system based on EMG signals for the Intelligent Sweet Home. The proposed system is applied to Intelligent Sweet Home which was developed to help the independence living of the elderly and physically handicapped individuals. The goal of proposed system is to control home-installed electronic devices such as TV, air-conditioner, curtain and lamp in Intelligent Sweet Home using EMG signals. Features such as VAR and DAMV having good separability performance are selected for pattern classification. FMMNN is adopted as a pattern classifier. Classification results are allowed to a developed remote control module and then corresponding infrared pulses can operate home-installed electronic devices. We concluded that EMG as an input interface for home-installed electronic devices in Intelligent Sweet Home.