• Journal of IKEEE
• /
• v.22 no.1
• /
• pp.156-161
• /
• 2018

Recently, as the population rapidly increases, food shortages and waste are emerging serious problem. In order to solve this problem, various countries and enterprises are trying research and product development such as a study of consumers' purchasing patterns of food and a development of smart refrigerator using IoT technology. However, the smart refrigerators which currently sold have high price issue and another waste due to malfunction and breakage by complicated configurations. In this paper, we proposed a low-cost smart refrigerator system based on IoT for solving the problem and efficient management of ingredients. The system recognizes and registers ingredients through QR code, image recognition, and speech recognition, and can provide various services of the smart refrigerator. In order to improve an accuracy of image recognition, we used a model using a deep learning algorithm and proved that it is possible to register ingredients accurately.

• The Journal of the Korea Contents Association
• /
• v.9 no.1
• /
• pp.465-474
• /
• 2009

The emergence of the digital age has changed the paradigm of education. Recently, the new paradigm needs new digital books that contain more interactive contents. Our goal is to design the digital textbook with convenient interfaces and cutting effects for interactive and effective education. To achieve these goals, we propose interfaces and contents which are designed after a lot of discussion with educational experts. In the implementation step, cutting algorithm is proposed to generate the cut planes of the 3D objects, based on the free strokes specified by the users. In order to test the performance of the contents, the testbed was implemented so that students try our digital book and present their evaluation results on the convenience and the effectiveness.

• The Journal of the Korea Contents Association
• /
• v.10 no.3
• /
• pp.444-453
• /
• 2010

The Knowledge and information are rapidly built through networks; and, through this, epochal changes and developments are reoccurring in diverse societal economic cultural ways. Especially, digital-education emerging together with educational environment changes is taking its place as an educational system which will be able to replace traditional education methods by overcoming the limitations of time and space held by present education methods. The role of GUI(Graphic User Interface) design, which adds user cognitive power and convenience as a method of purveying innumerous information, is growing. Consequently in this research, through the analysis of educational contents utilized in public organizations, research is performed regarding an educational content design for a more effective education of learners.

• Journal of the Korea Convergence Society
• /
• v.10 no.11
• /
• pp.55-61
• /
• 2019

In order to realize foreign language education, various existing educational media have been provided, but there are disadvantages in that the cost of the parish and the media program is high and the real-time responsiveness is poor. In this paper, we propose an artificial intelligence English conversation system based on VR and speech recognition. We used Google CardBoard VR and Google Speech API to build the system and developed artificial intelligence algorithms for providing virtual reality environment and talking. In the proposed speech recognition server system, the sentences spoken by the user can be divided into word units and compared with the data words stored in the database to provide the highest probability. Users can communicate with and respond to people in virtual reality. The function provided by the conversation is independent of the contextual conversations and themes, and the conversations with the AI assistant are implemented in real time so that the user system can be checked in real time. It is expected to contribute to the expansion of virtual education contents service related to the Fourth Industrial Revolution through the system combining the virtual reality and the voice recognition function proposed in this paper.

• Journal of Digital Convergence
• /
• v.19 no.9
• /
• pp.59-65
• /
• 2021

This study intends to find a positive effect on the learning of elementary school students by developing the exhibition contents of on-offline museum. This on-offline museum contents were combined with existing exhibit types and direct experience elements, and the theory of [blended learning]. Through this study, analyzing the limitations of existing online museum and finding with experiment to see if the new contents had a learning effect compared to the existing online museum. As a result of the experimental study, the content with a [direct experience] was counted as a high satisfaction and frequency index, and the [play] and [experience] type of direct experience contents showed higher satisfaction than the indirect experience type contents. Through this study, we want to provide new implications and development possibilities in the development of contents that online museums can provide, and to promote various effects on children's education.

• Journal of Digital Convergence
• /
• v.17 no.1
• /
• pp.179-187
• /
• 2019

Developing countries, including Africa, are experiencing very little human resources development due to the deprivation of equal educational opportunities, poor educational conditions, and the gap in information technology with developed countries. Developing countries that do not have excellent human resources are lagging behind in globalization competition with developed countries, and the problem of 'human resource development' in developing countries can not be avoided. In developing countries, education budgets are too low to meet education needs and compulsory education, and therefore they are not adequately responding to the increasing demand for education. The lack of education budget is due to the lack of education infrastructure. In this study, the NAS based server is configured to configure functions such as educational content and learning management, and the client area is presented with solutions for various media such as tablet, PC, and beam projector. And to support optimized e-learning services in developing countries by constructing a SCORM-based platform.

• Journal of Platform Technology
• /
• v.9 no.1
• /
• pp.32-39
• /
• 2021

Existing environmental measuring devices mainly focus on electromagnetic wave and eco-friendly product certification and durability test, and sensor reliability verification and verification of measurement data are conducted mainly through sensor performance evaluation through type approval and registration, acceptance test, initial calibration, and periodic test. This platform has established an ICT-based environmental monitoring sensor reliability verification system that supports not only performance evaluation for each target sensor, but also a verification system for sensor data reliability. A sensor board to collect sensor data for environmental information was produced, and a sensor and data reliability evaluation and verification service system was standardized. In addition, to evaluate and verify the reliability of sensor data based on ICT, a sensor data platform monitoring prototype using LoRa communication was produced, and the test was conducted in smart cities. To analyze the data received through the system, an optimization algorithm was developed using machine learning. Through this, a sensor big data analysis system is established for reliability verification, and the foundation for an integrated evaluation and verification system is provide.

• The Journal of Korean Institute of Information Technology
• /
• v.17 no.12
• /
• pp.81-92
• /
• 2019

Weeds are a major object which is very harmful to crops. To remove the weeds effectively, we have to classify them accurately and use herbicides. As computing technology has developed, image-based machine learning methods have been studied in this field, specially convolutional neural network(CNN) based models have shown good performance in public image dataset. However, CNN with numerous training parameters and high computational amount. Thus, it works under high hardware condition of expensive GPUs in real application. To solve these problems, in this paper, a hierarchical architecture based deep-learning model is proposed. The experimental results show that the proposed model successfully classify 21 species of the exotic weeds. That is, the model achieve 97.2612% accuracy with a small number of parameters. Our proposed model with a few parameters is expected to be applicable to actual application of network based classification services.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.05a
• /
• pp.478-480
• /
• 2022

Smart Railway as a next generation railway technology is expected to have rapid evolution with developments of information and communications tehchology. Especially, smart railway will be progressed more evolved transportation means for railway operation and costomer service based with spread of commercial 5G communication. So, it is very important to investigate and analyze trends of smart railway related tehcnology of 5G mobile communication for samrt railway infra structure, server technolgy for AI, big data, deep learning, information security technology, sensor and IoT. In this paper, 5G based communicaion technology and application techology related smart railway is described and trends of new techlogy on this communication tehnology is investigated. The results of this study can be used for smart railway study and implementation, research and development for smart railway communicaion technology, etc.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.05a
• /
• pp.209-211
• /
• 2022

YouTube, a video platform used by millions of people worldwide, provides a rapidly growing video service. This study aims to understand the characteristics and cultural differences of each country using the Kaggle dataset, one of the public datasets, and to show the usefulness of the public dataset. For this purpose, we analyze data from 11 countries, 15 categories, and about 1.1 million trending videos. This study adopts Python to obtain the number of videos by category for data analysis, the selection period of videos rapidly increasing in popularity, and the ratio of unique videos. In the future, based on machine learning, we plan to research to help diagnose individual videos and establish channel operation plans and strategies by predicting the selection possibility and selection period based on machine learning.