• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.3
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• pp.379-385
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• 2012

This paper developes the navigation visual aid supporting a watch officer's situation awareness and analyzes its performance test result. Developing the equipment made from composite video sensor which transfer video signal, ranger laser measurement model which search out distance, Pan/ Tilt, center control device. The developed equipment with Pan/Tilt was made from high performance video sensor and ranger laser measurement. To make a real ship test, we carried on setting the developed equipment on ship, observed a danger factor and analyzed a image, and from that we can evaluate marine environment awareness. Through this result, the developed equipment can show effective ability of the awareness of the clearer check and resolution situation when compare with the binocular.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.5
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• pp.170-179
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• 2008

The disabled and elderly people have a wide variety of functional impairments. By disability and elderly user group definition identification of users needs and specification of emergency support system were studied. Existing technologies including location navigation and information exchange devise and communication systems were analyzed to design proper integrated system for emergency situations. There are two types of services considered in the project: assisted living services(ALS) including health and emergency needs and assisted mobility services(AMS) with transportation needs. To develop emergency support system, functional identification and requirements was studied through the analysis of existing emergency system and organization. The 4-step emergency management scheme was developed to preactive emergency service which include emergency detection identification, response and follow-up steps.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.4
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• pp.167-178
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• 2023

Our society is rapidly changing, and there is a growing demand for various convenience services in our daily lives. Among these services, railway and subway stations require tailored wayfinding services to accommodate individuals with disabilities. Currently, signage and information desks are the primary means of navigation. However, individuals with disabilities often rely on assistance from others due to physical discomfort or cognitive impairments. In this paper, we propose a customized wayfinding system within railway stations to assist individuals with disabilities. This system aims to ensure safe and convenient mobility in complex indoor environments, including transfer facilities.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.157-167
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• 2023

The use of big data for transportation often involves using data that includes personal information, such as the driver's driving routes and coordinates. This study explores the creation of a route choice prediction model using a large dataset from mobile navigation apps using federated learning. This privacy-focused method used distributed computing and individual device usage. This study established preprocessing and analysis methods for driver data that can be used in route choice modeling and compared the performance and characteristics of widely used learning methods with federated learning methods. The performance of the model through federated learning did not show significantly superior results compared to previous models, but there was no substantial difference in the prediction accuracy. In conclusion, federated learning-based prediction models can be utilized appropriately in areas sensitive to privacy without requiring relatively high predictive accuracy, such as a driver's preferred route choice.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.3
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• pp.11-18
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• 2016

Since GNSS signals get blocked by buildings in urban canyons or narrow alleys, it is very difficult to secure a enough number of visible satellites for satellite navigation in those poor signal-reception environments. In those situations, one cannot get their coordinates or obtain accurate positions. In this study, a couple of strategies for improving positioning accuracy in urban canyons were developed and their performance was verified. First of all, we combined GPS and GLONASS measurements together and devised algorithms to quality-control observed signals and eliminate outliers. Also, a new multipath reduction scheme was applied to minimize its effect by utilizing SNR values of the observed signals. For performance verification of the developed technique, a narrow alley of 10m width located near the back gate of the Inha University was selected as the test-bed, and then we conducted static and kinematic positioning at four pre-surveyed points. We found that our new algorithms produced an 45% improvement in an open-sky environment compared with the positioning result of a low-cost u-blox receiver. In the alleys, 3-D accuracy improved by an average of 37%. In the case of kinematic positioning, especially, biases showing up in regular receivers got eliminated significantly through our new filtering algorithms.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.200-201
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• 2023

Digital twin technology is used in various fields as a method of creating a virtual world to minimize the cost of solving problems in the real world, and is also actively used in the maritime field, such as large-scale systems such as ships and offshore plants. In this paper, we tried to build a digital twin of coastal waters using a ship-handling simulator. The digital twin of the coastal waters developed in this way can be used to safely manage Korea's coastal waters, where maritime traffic is complicated, by providing a actual maritime traffic data. It can be usefully used to develop and advance technologies related to maritime autonomous surface ships and intelligent maritime traffic information services in coastal waters. In addition, it can be used as a 3D-based monitoring equipment for areas where physical monitoring is difficult but real-time maritime traffic monitoring is necessary, and can provide functions to safely manage maritime traffic situations such as aerial views of ports/control areas, bridge views/blind sector views of ships in operation.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.438-444
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• 2004

The intelligent robots that will be needed in the near future are human-friendly robots that are able to coexist with humans and support humans effectively. To realize this, robots need to recognize their position and posture in known environment as well as unknown environment. Moreover, it is necessary for their localization to occur naturally. It is desirable for a robot to estimate of his position by solving uncertainty for mobile robot navigation, as one of the best important problems. In this paper, we describe a method for the localization of a mobile robot using image information of a moving object. This method combines the observed position from dead-reckoning sensors and the estimated position from the images captured by a fixed camera to localize a mobile robot. Using the a priori known path of a moving object in the world coordinates and a perspective camera model, we derive the geometric constraint equations which represent the relation between image frame coordinates for a moving object and the estimated robot's position. Since the equations are based or the estimated position, the measurement error may exist all the time. The proposed method utilizes the error between the observed and estimated image coordinates to localize the mobile robot. The Kalman filter scheme is applied for this method. its performance is verified by the computer simulation and the experiment.

• Journal of information and communication convergence engineering
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• v.5 no.2
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• pp.171-176
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• 2007

To give a guarantee a consistently high level of quality and reliability of Telematics traffic service, traffic flow forecasting is very important issue. In this paper, we proposed an adaptable integrated prediction model to predict the traffic flow in the future. Our model combines two methods, short-term prediction model and long-term prediction model with different combining coefficients to reflect current traffic condition. Short-term model uses the Kalman filtering technique to predict the future traffic conditions. And long-term model processes accumulated speed patterns which means the analysis results for all past speeds of each road by classifying the same day and the same time interval. Combining two models makes it possible to predict future traffic flow with higher accuracy over a longer time range. Many experiments showed our algorithm gives a better precise prediction than only an accumulated speed pattern that is used commonly. The result can be applied to the car navigation to support a dynamic shortest path. In addition, it can give users the travel information to avoid the traffic congestion areas.

• International Journal of Control, Automation, and Systems
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• v.1 no.1
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• pp.134-141
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• 2003

A major research issue associated with service robots is the creation of an environment recognition system for mobile robot navigation that is robust and efficient on various environment situations. In recent years, intelligent autonomous mobile robots have received much attention as the types of service robots for serving people and industrial robots for replacing human. To help people, robots must be able to sense and recognize three dimensional space where they live or work. In this paper, we propose a three dimensional environmental modeling method based on an edge enhancement technique using a planar fitting method and a neural network technique called "Growing Neural Gas Network." Input data pre-processing provides probabilistic density to the input data of the neural network, and the neural network generates a graphical structure that reflects the topology of the input space. Using these methods, robot's surroundings are autonomously clustered into isolated objects and modeled as polygon patches with the user-selected resolution. Through a series of simulations and experiments, the proposed method is tested to recognize the environments surrounding the robot. From the experimental results, the usefulness and robustness of the proposed method are investigated and discussed in detail.in detail.

• The Journal of Korea Robotics Society
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• v.2 no.4
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• pp.334-340
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• 2007

This paper introduces a prototype smart home environment that is built in the research building to demonstrate the feasibility of a robot-assisted future home environment. Localization, navigation, object recognition and handling are core functionalities that an intelligent service robot should provide. A huge amount of research effort has been made to make the service robot perform these functions with its own sensors, actuators and a knowledge base. With all complicated configuration of sensors, actuators and a database, the robot could only perform the given tasks in a predefined environment or show the limited capabilities in a natural environment. We started a smart home environment for service robots for simple service robots to provide reliable services by communicating with the environment through the wireless sensor networks. In this paper, we introduce various types of smart devices that are developed for assisting the robot in the environment by providing sensor and actuator capabilities. In addition, we present how the devices are integrated to constitute the smart home environment for service robots.