• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.3
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• pp.1-14
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• 2019

The 4th Industrial Revolution, intelligent automobile application technology is evolving beyond the limit of the mobile device to a variety of application software and multi-media collective technology with big data-based AI(artificial intelligence) technology. with the recent commercialization of 5G mobile communication service, artificial intelligent automobile technology, which is a fusion of automobile and IT technology, is evolving into more intelligent automobile service technology, and each multimedia platform service and application developed in such distributed environment is being developed Accordingly, application software technology developed with a single system SoC of a portable terminal device through various service technologies is absolutely required. In this paper, smart device design for ontology design of intelligent automobile open platform enables to design intelligent automobile middleware software design technology such as Android based SVC Codec and real time video and graphics processing that is not expressed in single ASIC application software technology as SoC based application designWe have experimented in smart device environment through researches, and newly designed service functions of various terminal devices provided as open platforms and application solutions in SoC environment and applied standardized interface analysis technique and proved this experiment.

• The Journal of Korea Robotics Society
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• v.17 no.2
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• pp.142-151
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• 2022

With the advent of the 4th industrial revolution, autonomous driving technology is being commercialized in various industries. However, research on autonomous driving so far has focused on platforms with wheel-type platform. Research on a tracked platform is at a relatively inadequate step. Since the tracked platform has a different driving and steering method from the wheel-type platform, the existing research cannot be applied as it is. Therefore, a path-tracking algorithm suitable for a tracked platform is required. In this paper, we studied a path-tracking algorithm for a tracked platform based on a GPS sensor. The existing Pure Pursuit algorithm was applied in consideration of the characteristics of the tracked platform. And to compensate for "Cutting Corner", which is a disadvantage of the existing Pure Pursuit algorithm, an algorithm that changes the LAD according to the curvature of the path was developed. In the existing pure pursuit algorithm that used a tracked platform to drive a path including a right-angle turn, the RMS path error in the straight section was 0.1034 m and the RMS error in the turning section was measured to be 0.2787 m. On the other hand, in the variable LAD algorithm, the RMS path error in the straight section was 0.0987 m, and the RMS path error in the turning section was measured to be 0.1396 m. In the turning section, the RMS path error was reduced by 48.8971%. The validity of the algorithm was verified by measuring the path error by tracking the path using a tracked robot platform.

• Journal of Christian Education in Korea
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• v.66
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• pp.309-341
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• 2021

The purpose of this study is to develop an intelligent learning platform model for faith education in preparation for the post-corona era. This study reviewed artificial intelligence algorithms, research on learning platform development, and prior research related to faith education. The draft of the intelligent learning platform design model was developed by synthesizing previous studies. The developed draft model was validated by a Delphi survey targeting 5 experts. The content validity of the developed draft model was all 1. This is the validation of the draft model. Three revised opinions of experts were presented on the model. And the model was revised to reflect the opinions of experts. The modified final model consisted of three areas: learning materials, learning activities, learning data, and artificial intelligence. Each area is composed of 9 elements of curriculum, learning content additional learning resources, learner type, learning behavior, evaluation behavior, learner characteristic data, learning activity data, artificial intelligence data, and learning analysis. Each component has 29 sub-elements. In addition, 14 learning floors were formed. The biggest implication of this study is the first development of a basic model of an intelligent learning platform for faith education.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.89-93
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• 2009

Embedded systems are becoming more popular as many embedded platforms have become more affordable. It offers a compact solution for many different problems including computer vision applications. Texture classification can be used to solve various problems, and implementing it in embedded platforms will help in deploying these applications into the market. This paper proposes to deploy the texture classification algorithms onto the embedded computer vision (ECV) platform. Two algorithms are compared; grey level co-occurrence matrices (GLCM) and Gabor filters. Experimental results show that raw GLCM on MATLAB could achieves 50ms, being the fastest algorithm on the PC platform. Classification speed achieved on PC and ECV platform, in C, is 43ms and 3708ms respectively. Raw GLCM could achieve only 90.86% accuracy compared to the combination feature (GLCM and Gabor filters) at 91.06% accuracy. Overall, evaluating all results in terms of classification speed and accuracy, raw GLCM is more suitable to be implemented onto the ECV platform.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.2
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• pp.156-163
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• 2002

This paper presents a new formulation to simplify the three resulting constraint equations of the direct kinematics of the 3-6 (Stewart-Gough) Platform. The conventional direct kinematics of the 3-6 Platform has been formulated through complicated steps with trigonometric functions in three angle variables and thus results in the computational burden. In order to reduce the formulation complexity, we replace an angle variable into a length one and express three connecting joints on the moving platform in the same frame. The proposed formulation yields considerable abbreviation of the number of the calculation terms involved in the direct kinematics. It is verified through a series of simulation results.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.4
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• pp.260-267
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• 2015

In the past, we implemented a web-based smart education platform, but this is not efficient in a smart or mobile education environment. Therefore, in this paper, we propose an Android-based e-board smart platform for a smart or mobile education system. Here, we use Anoto digital pen- and dot pattern-based technologies. This Android-based smart education platform is efficient for a smart education environment. Further, we implement the hardware and software parts of the technologies, an Anoto-based trajectory recognition algorithm, and a probabilistic neural network for handwritten digit and hand gesture recognition.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.232-235
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• 2003

In this paper, we implemented a FIPA-OS multi-agent framework bundle in OSGi Service Platform. FIPA-OS is an open agent platform for constructing FIPA compliant agent using mandatory components that required by all FIPA-OS agents to execution and optional components that FIPA-OS agent car optionally use. The platform supports communication between multiple agents and communication language which conforms to the FIPA standards. FIPA-OS framework bundle is composed of DE(Directory Facilitator), AMS(Agent Management System), ACC(Agent Communication Channel) and MTS(Message Transport System) bundle. These bundles installed in the OSGi service platform and their life cycle can be managed by the framework.

• Journal of Korea Multimedia Society
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• v.20 no.9
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• pp.1519-1526
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• 2017

The existing DSRC(Dedicated Short Range Communication) scheme has a limitation in providing various services through short-range wireless communication. Therefore, it is necessary to develop an intelligent WAVE/DSRC hybrid wireless platform that can improve data transmission speed and extend the effective communication range. This paper introduces WAVE/DSRC integrated platform technology using WAVE(Wireless Access in Vehicle Environments) to overcome the disadvantages of DSRC. First, the desinged software configuration of the WAVE/DSRC integrated platform is described. Then each task operation scheme and WAVE software design are described. By applying the WAVE/DSRC integrated platform, we can compensate the shortcomings of DSRC. It can provide more accurate and reliable services.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.4
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• pp.27-33
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• 2018

The recent efforts in academia and industry represent a paradigm shift that will extend the IoT from the home environment so that it is interoperable with the Internet of Vehicles (IoV). IoV is a special kind of IoT. It allows to connect between vehicle and things located in infrastructure. Furthermore, IoV enable to create new intelligent services through collaboration with existing various services such as smart city and connected home. In this paper, we develop a service in order to realize IoV. To this end, we design a novel vehicle service platform which could automatical controlling the IoT device according to drivers' voice. To show practical usability of our proposed platform, we develop a prototype service could be call car-to-thing (C2T). We expect that our proposed platform could eventually contribute to realizing IoV.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.5
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• pp.1047-1049
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• 2009

This paper presents an intelligent electronic device(IED) platform which is based on a new frequency estimation algorithm. The IED platform features not only the accurate estimation of frequency but also the fast network-based transmisstion of fault data and waveforms. The simulation results show that the proposed frequency estimation algorithm improves convergence speed, and has lower frequency estimation error compared with those of conventional algorithms. The network-based IED is designed to ensure transmission latency being less than 1.0% of sampling interval.