• Journal of IKEEE
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• v.24 no.2
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• pp.392-402
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• 2020

This paper proposes a solar tracking system without photo-sensors. The system can be classified into four modules: Solar Tracking, MPPT, ESS, and Real-Time Monitoring. Nine solar panels, as a basic unit, are adopted with grid structures of different heights to reduce wind influence and to enable solar tracking without photo-sensors. The low-cost MCU implements MPPT method which generates PWM switching signal for boost converter. The unit of ESS consists of three-series and four-parallel lithium-ion batteries in order to enable monitoring for abnormalities in temperature and electrical characteristics of battery. Four MCUs used in the system consists of two AVR Atmega128, and two Raspberry PI, and they exchanges operation informations. Experimental results of the proposed system show the solar tracking performance, the possibility of on-site and remote monitoring and the convenience of maintenance based on IoT technology.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.3
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• pp.127-141
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• 2014

A Vehicle Tracking System consists of GPS tracking device which fits into the vehicle and captures the GPS location information at regular intervals to a central GIS server, and GIS tracking server providing three major responsibilities: receiving data from the GPS tracking unit, securely storing it, and serving this information on demand of the user. GPS based tracking systems supporting a multi-session processing among RMA, RM, and RCP can make a quick response to various services including other vehicle information between RSU and OBU on demand of the user. In this paper we design RSU lower layers and RCP applications in OBU for a multisession processing simulation and test message processing transactions among RMA-RM and RM-RCP. Furthermore, we implement the additional functions of handling access commands simultaneously on multiple service resources which are appropriate for the experimental testing conditions. In order to make a multi-session processing test, it reads 30 resource data,0002/0001 ~ 0002/0030, in total and then occurs 30 session data transmissions simultaneously. We insert a sequence number field into a special header of dummy data as a corresponding response to check that the messages are received correctly. Thus, we find that GIS service system with a multi-session processing is able to provide additional 30 services in a same speed of screen presentation loading while identifying the number of session processing of Web GIS service, the number of OBU service, and the speed of screen presentation loading by comparing a single session and a multi-session of GIS service system.

• Journal of the Korea Institute of Building Construction
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• v.10 no.3
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• pp.65-70
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• 2010

Steel frame construction in high places entails many risk factors. In order to improve the safety and productivity of steel frame construction, a project to develop a robotic tower-crane has been undertaken. As the first step, a real-time lifting-path tracking system is being developed. In a previous study, a laser-based tracking system was proposed. While a laser-based tracking system requires at least three laser sensors to detect the x, y, z coordinates of a lifted steel member, a GPS-based system has an advantage over the laser-based system, in that the x, y, z coordinates of a lifted steel member can be detected by a single GPS sensor. To improve the accuracy, arelative positioning method using two GPS sensors was proposed in a previous study. This paper reports an improved GPS-based lifting-path tracking system of a tower crane based on an integrated RF modem and GPS system. The results showedthat the RF modem could successfully send the identifier information to a server a maximum distance of 1 km away from the lifted steel beam, and the lifting path information of each beam captured by the GPS-based tracking system was successfully saved together. Also, byusing an improved algorithm for the GPS relative positioning method, the deviation was reduced to 0.61 m on average.

• Journal of KIISE:Software and Applications
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• v.34 no.10
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• pp.937-944
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• 2007

In this paper, we propose multiple human tracking with an moving stereo camera. The tracking process is based on mean shift algorithm which is using color information of the target. Color based tracking approach is invariant to translation and rotation of the target but, it has several problems. Because of mean shift uses color distribution, it is sensitive to color distribution of background and targets. In order to solve this problem, we combine color and depth information of target. Also, we build human body part model to handle occlusions and we have created adaptive box scale. As a result, the proposed method is simple and efficient to track multiple humans in real time.

• Korean Journal of Applied Biomechanics
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• v.17 no.1
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• pp.81-90
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• 2007

The effort identifying positioning information of the moving object in real time has been a issue not only in sport biomechanics but also other academic areas. In order to solve this issue, this study tried to track the movement of a pitched ball that might provide an easier prediction because of a clear focus and simple movement of the object. Machine learning has been leading the research of extracting information from continuous images such as object tracking. Though the rule-based methods in artificial intelligence prevailed for decades, it has evolved into the methods of statistical approach that finds the maximum a posterior location in the image. The development of machine learning, accompanied by the development of recording technology and computational power of computer, made it possible to extract the trajectory of pitched baseball from recorded images. We present a method of baseball tracking, based on object tracking methods in machine learning. We introduce three state-of-the-art researches regarding the object tracking and show how we can combine these researches to yield a novel engine that finds trajectory from continuous pitching images. The first research is about mean shift method which finds the mode of a supposed continuous distribution from a set of data. The second research is about the research that explains how we can find the mode and object region effectively when we are given the previous image's location of object and the region. The third is about the research of representing data into features that we can deal with. From those features, we can establish a distribution to generate a set of data for mean shift. In this paper, we combine three works to track baseball's location in the continuous image frames. From the information of locations from two sets of images, we can reconstruct the real 3-D trajectory of pitched ball. We show how this works in real pitching images.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.4 s.316
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• pp.67-73
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• 2007

An optical pick up generally has coupled dynamics between focusing and tracking servos. The coupled dynamics reduces tracking performance of optical disk drives. A conventional control method is holding the previous tracking control command in the presence of surface defect. The method has a long settling time. If the defective area is getting larger, objective lens will get away from the following track. In order to overcome this problem, this paper proposed a new control method for optical disk drives based on a prediction of tracking error and focusing error. We present how to compensate the coupled dynamics so that reduced setting time is achieved. It is verified by experiments that the proposed method brings an improved performance in the presence of surface defect as well as in the normal operating condition.

• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.1
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• pp.47-60
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• 2018

In this paper, we proposed a method for eliminating aiming error of unguided anti-tank rocket using improved target tracking. Since predicted fire is necessary to hit moving targets with unguided rockets, a method was proposed to estimate the position and velocity of target using fire control system. However, such a method has a problem that the hit rate may be lowered due to the aiming error of the shooter. In order to solve this problem, we used an image-based target tracking method to correct error caused by the shooter. We also proposed a robust tracking method based on TLD(Tracking Learning Detection) considering characteristics of the FCS(Fire Control System) devices. To verify the performance of our proposed algorithm, we measured the target velocity using GPS and compared it with our estimation. It is proved that our method is robust to shooter's aiming error.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.195-198
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• 2013

Recognition and Tracking of interesting object is the significant field in Computer Vision. Mean-Shift algorithm have chronic problems that some errors are occurred when histogram of tracking area is similar to another area. in this paper, we propose to solve the problem. Each algorithm blocks skin color filtering, face detect and Mean-Shift started consecutive order assists better operation of the next algorithm. Avoid to operations of the overhead of tracking area similar to a histogram distribution areas overlap only consider the number of white pixels by running the Viola-Jones algorithm, simple arithmetic increases the convergence of the Mean-Shift. The experimental results, it comes to 78% or more of white pixels in the Mean-Shift search area, only if the recognition of the face area when it is configured to perform a Viola-Jones algorithm is tracking the object, was 100 percent successful.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.4
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• pp.135-144
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• 2018

The domestic pigsty environment is highly vulnerable to the spread of respiratory diseases such as foot-and-mouth disease because of the small space. In order to manage this issue, a variety of studies have been conducted to automatically analyze behavior of individual pigs in a pig pen through a video surveillance system using a camera. Even though it is required to correctly segment touching pigs for tracking each pig in complex situations such as aggressive behavior, detecting the correct boundaries among touching pigs using Kinect's depth information of lower accuracy is a challenging issue. In this paper, we propose a segmentation method using motion information of the touching pigs. In addition, our proposed method can be applied for detecting tracking errors in case of tracking individual pigs in the complex environment. In the experimental results, we confirmed that the touching pigs in a pig farm were separated with the accuracy of 86%, and also confirmed that the tracking errors were detected accurately.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.250-256
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• 2009

This paper presents a robotic tower-crane system using encoder and gyroscope sensors as path tracking devices. Tower crane work is often associated with falling accidents and industrial disasters. Such problems often incur a loss of time and money for the contractor. For this reason, many studies have been done on an automatic tower crane. As a part of 5-year 23-million-dollar research project in Korea, we are developing a robotic tower crane which aims to improve the safety level and productivity. We selected a luffing tower crane, which is commonly used in urban construction projects today, as a platform for the robotic tower crane system. This system comprises two modules: the automated path planning module and the path tracking module. The automated path planning system uses the 3D Cartesian coordinates. When the robotic tower crane lifts construction material, the algorithm creates a line, which represents a lifting path, in virtual space. This algorithm seeks and generates the best route to lift construction material while avoiding known obstacles from real construction site. The path tracking system detects the location of a lifted material in terms of the 3D coordinate values using various types of sensors including adopts encoder and gyroscope sensors. We are testing various sensors as a candidate for the path tracking device. This specific study focuses on how to employ encoder and gyroscope sensors in the robotic crane These sensors measure a movement and rotary motion of the robotic tower crane. Finally, the movement of the robotic tower crane is displayed in a virtual space that synthesizes the data from two modules: the automatically planned path and the tracked paths. We are currently field-testing the feasibility of the proposed system using an actual tower crane. In the next step, the robotic tower crane will be applied to actual construction sites with a following analysis of the crane's productivity in order to ascertain its economic efficiency.