• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.4
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• pp.695-702
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• 2022

Smart railway system, which has been actively studied in recent years, is entering the intelligent stage beyond the automation stage based on ICT (Information & Communication Technology) such as communication technology and information technology. ICT technology used in smart railways is generally supported by various information protection technologies as it is vulnerable to information infringement. As a means of high-speed/mass transportation, it is essential to devise an information protection plan for ICT technology that forms the basis for smartening the railway system. Therefore, this paper presents the necessity of step-by-step information protection that measures for smart railway communication by examining potential risk factors of smart railway communication base and considering information protection factors that can respond to them.

• ETRI Journal
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• v.44 no.4
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• pp.641-653
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• 2022

In the process of autonomous vehicle motion planning and to create comfort for vehicle occupants, factors that must be considered are the vehicle's safety features and the road's slipperiness and smoothness. In this paper, we build a mathematical model based on the combination of a genetic algorithm and a neural network to offer lane-change solutions of autonomous vehicles, focusing on human vehicle control skills. Traditional moving planning methods often use vehicle kinematic and dynamic constraints when creating lane-change trajectories for autonomous vehicles. When comparing this generated trajectory with a man-generated moving trajectory, however, there is in fact a significant difference. Therefore, to draw the optimal factors from the actual driver's lane-change operations, the solution in this paper builds the training data set for the moving planning process with lane change operation by humans with optimal elements. The simulation results are performed in a MATLAB simulation environment to demonstrate that the proposed solution operates effectively with optimal points such as operator maneuvers and improved comfort for passengers as well as creating a smooth and slippery lane-change trajectory.

• Annual Conference of KIPS
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• 2011.04a
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• pp.1218-1221
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• 2011

The development of the internet and information management has enabled new applications which include: Electronic medical record (EMR), intelligent transportation, environmental monitoring, etc. In this paper, we design and implement the Continuity Care Record(CCR) Data Stream management server that compiled with DSMS and DBMS in EMR system for processing, monitoring the incoming CCR data stream and storing the processed result with high-efficiency. The proposed system enables users not only to query stored CCR information from DBMS, but also enables to execute continue query for the real-time CCR Data Stream. By using of CCR Viewer Application users can view or update their personal health records even compare self health care records with standard health care records in order to monitor the healthy status, and the on line updating information would be minimized and medical error.

• Journal of the Korea Society of Computer and Information
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• v.14 no.7
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• pp.151-160
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• 2009

The aim of this study is to propose economical driving speed index which those are geometric road status; assess the levels of which those cost-benefit of driving energy consumption and emission; are search road safety design and operational technology for driving simulator. For the objective, we analyzed the current status of driving energy consumption and driving scenarios by the road alignments, and reviewed driving and technical specifications by the geometric types of road according to the implementation, and extended completion. Throughout the result of this study, diverse related driving information provision service, efficiently navigation driving module is expected to be implemented in the national highway design system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.317-319
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• 2021

In Korea, an intelligent transportation system(ITS) is established to efficiently operate traffic congestion on roads and is being used for traffic information collection and speed control systems. Currently, designated and dedicated lanes are in place to ensure traffic circulation and traffic safety, and systematic and accurate illegal vehicle crackdown systems with artificial intelligence technology are needed. In this study, we propose a vehicle number recognition model that can improve the efficiency of the traffic of designated vehicles. By applying computer vision technology, we are going to identify three-lane and four-lane multi-lane roads in real time and detect vehicle numbers by car to suggest ways to crack down on vehicles that violate the designated lane system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1708-1734
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• 2022

In the development of logistics system, the breakthrough of important technologies such as technology platform for logistics information management and control is the key content of the study. Based on Javascript and JQuery, the logistics system realizes real-time monitoring, collection of historical status data, statistical analysis and display, intelligent recommendation and other functions. In order to strengthen the cooperation of warehouse storage, enhance the utilization rate of resources, and achieve the purpose of real-time and visual supervision of transportation equipment and cargo tracking, this paper studies the VNF dynamic deployment and SFC routing problem in the network load change scenario based on the logistics system. The BIP model is used to model the VNF dynamic deployment and routing problem. The optimization objective is to minimize the total cost overhead generated by each SFCR. Furthermore, the application of the SFC mapping algorithm in the routing topology solving problem is proposed. Based on the concept of relative cost and the idea of topology transformation, the SFC-map algorithm can efficiently complete the dynamic deployment of VNF and the routing calculation of SFC by using multi-layer graph. In the simulation platform based on the logistics system, the proposed algorithm is compared with VNF-DRA algorithm and Provision Traffic algorithm in the network receiving rate, throughput, path end-to-end delay, deployment number, running time and utilization rate. According to the test results, it is verified that the test results of the optimization algorithm in this paper are obviously improved compared with the comparison method, and it has higher practical application and promotion value.

• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.307-309
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• 2024

세계적으로 물류 자동화 시장은 2026년까지 약 44조원으로 예상되며, 연평균 10.6%의 성장률을 기록할 것으로 예측된다. 특히 국내 시장은 2025년까지 연평균 성장률 11.5%로 1조원 이상으로 전망되고 있다. 2025년까지 물류 자동화 시장은 270억 달러로 급성장할 것으로 예상되며, 반도체 분야에서 로봇이 상품 입고, 보관, 상품 피킹, 분류, 출고 작업을 담당하는 트렌드가 강조된다. 본 논문은 반도체 물류 분야를 대상으로 작은 크기와 민첩성을 갖춘 로봇을 개발하여 작업 공간을 효율적으로 활용하고 인력을 최소화하려는 목적이다. 수직 및 수평 로봇은 효율적인 자동화 시스템을 제공하며, UI를 사용하여 AGV, 선반, 스카라 로봇을 하나의 통합 시스템으로 개발하고자 한다. 특히 코드 인식, 초음파 센서, 아두이노 MCU, 스카라 로봇, AGV 등을 활용한 로봇 시스템을 개발하여 반도체 물류 작업을 효율적으로 수행하고자 한다. 다양한 분야에서 활용 가능한 스카라 로봇을 개발하기 위해 마이크로 스텝과 풀리, 타이밍 벨트를 이용한 구동 방식 등을 채택한다. 반도체 물류 센터에서의 자동화는 물류 공간의 확대와 인건비 절감을 기대할 수 있으며, 로봇 및 드론을 활용하여 인건비 절감과 효율성 향상을 통해 기업 비용 절감에 기여할 것으로 예상된다.

• Nuclear Engineering and Technology
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• v.56 no.10
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• pp.4227-4236
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• 2024

Nuclear energy is used more and more widely as a clean energy source, but nuclear energy facilities are risky, and when a nuclear leak occurs, it is necessary to detect equipment in a nuclear radiation environment. In the nuclear radiation environment, due to the impact of high-energy particles on the camera sensor, the collected image contains a lot of radiation noise, which greatly reduces the visual perception of the image. Aiming at the problem that radiation noise reduces image quality, a radiation image compound filtering algorithm combining median filtering and multi-frame average filtering is proposed based on radiation noise characteristics. Compared with several common filtering algorithms, the radiation noise image is filtered under the same radiation dose and achieve the highest Peak Signal Noise Rate (PSNR) and Structural Similarity (SSIM), and compared with the multi-frame average filtering method, the number of image frames required by the algorithm in this paper is greatly reduced. Experimental results show that the algorithm can effectively eliminate radiation noise and is more suitable for image filtering in radiation environment.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.6
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• pp.74-83
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• 2011

The high-pass transportation information system directly collects section information by using probe cars and therefore can offer more reliable information to drivers. However, because the running condition and features of probe cars and statistical processing methods affect the reliability of the information and particularly because the section travel time is greatly influenced by whether there has been delay by signals on urban roads or not, there can be much deviation among the collected individual probe data. Accordingly, researches in multilateral directions are necessary in order to enhance the credibility of the section information. Yet, the precedent studies related to high-pass information provision have been conducted on the highway sections with the feature of continuous flow, which has a limit to be applied to the urban roads with the transportational feature of an interrupted flow. Therefore, this research aims at analyzing the features of high-pass transportation data on urban roads and finding a proper processing method. When the characteristics of the high-pass data on urban roads collected from RSE were analyzed by using a time-space diagram, the collected data was proved to have a certain pattern according to the arriving cars' waiting for signals with the period of the signaling cycle of the finish node. Moreover, the number of waiting for signals and the time of waiting caused the deviation in the collected data, and it was bigger in traffic jam. The analysis result showed that it was because the increased number of waiting for signals in traffic jam caused the deviation to be offset partially. The analysis result shows that it is appropriate to use the mean of this collected data of high-pass on urban roads as its representative value to reflect the transportational features by waiting for signals, and the standard of judgment of delay and congestion needs to be changed depending on the features of signals and roads. The results of this research are expected to be the foundation stone to improve the reliability of high-pass information on urban roads.