• Smart Media Journal
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• v.7 no.2
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• pp.47-53
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• 2018

Along with the development of information and communication technology, smart education that can learn without restrictions of time, place and equipment is activated even in the field of education. Although smart education is provided with content-based training solutions, construction of a system that grasps individual characteristics of learners and provides personalized learning is relatively weak. The activity of free choice is an important play activity of early childhood education, but it is not implemented efficiently by relying on the clinical observation of the teacher. If the IoT(Internet of Things) technology based on Hyper-Connected is applied to free-choice activities, it is possible to provide the child's personalized activity type and play-form analysis based on objective and stylized data. In this paper, we design and implement a system to monitor the child's activity of free choice by building an IoT environment that is based on open source hardware. The proposed system provides children's activity information as objective data and will be used as teacher's work mitigation and custom training material for each child.

• The Journal of the Korea Contents Association
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• v.18 no.1
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• pp.250-257
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• 2018

Today, the integration of the rapid development of ICT and the smart devices moves our lives quickly into an online community environment through not only quick and easy information search but also various social media. Accordingly, individual activities in the smart media environment are pouring out vast quantities of data in many fields, accumulating a tremendous amount of data. The everyday data of individuals is reproducing different values from the previous ones, while suggesting new customized services that utilize them in various fields. Recently, big data utilization has attracted a great attention in the field of healthcare. Especially, development of healthcare service linked with mobile is expected to bring a new paradigm in this field. In this study, creation of a 3D avatar character model as a means to transfer information to individuals more efficiently is proposed in the development of mobile customized service for health promotion and growth prediction of children and adolescents, at the same time, an effective visual expression method to have a sense of immersion and unity is searched.

• Smart Media Journal
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• v.7 no.2
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• pp.54-59
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• 2018

With the increasing use of touch-enabled mobile devices such as smartphones and tablet PCs, the works are done on desktop computers and smartphones, and tablet PCs perform laptops. However, due to the nature of smart devices that require portability, QWERTY keyboard is densely arranged in a small screen. This is the cause of different typographical errors when using the mechanical QWERTY keyboard. Unlike the mechanical QWERTY keyboard, which has enough space for each button, QWERTY keyboard on the touch screen often has a small area assigned to each button, so that it is often the case that the surrounding buttons are input rather than the button the user intends to press. In this paper, we propose a method to automatically correct the input errors of the QWERTY keyboard in the touch screen environment by using the n-gram language model using the word unigram and the bigram probability.

• Journal of Digital Convergence
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• v.17 no.7
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• pp.311-316
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• 2019

The mobile game environment is rapidly expanding with AR (augmented reality) technology along with artificial intelligence. In particular, AR (Augmented Reality) technology is a field of VR (Virtual Reality), which is a technology that shows a mixture of virtual information and images in a real environment. Recently, research on mobile UI design based on the interaction based on the augmented reality technology has become important at the point when various utilization methods are suggested based on understanding of contents. There are still some issues in terms of whether the consumer can utilize it in various ways, unlike the developed supply system. In this paper, we present an example of mobile UI design based on interaction based on smart media augmented reality through previous study and literature study of smart augmented reality to solve problem UI issues based on background theory.

• Journal of Broadcast Engineering
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• v.24 no.7
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• pp.1266-1275
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• 2019

With increasing criminal rates and number of CCTVs, much attention has been paid to intelligent surveillance system on the horizon. Object detection and tracking algorithms have been developed to reduce false alarms and accurately help security agents immediately response to undesirable changes in video clips such as crimes and accidents. Many studies have proposed a variety of algorithms to improve accuracy of detecting and tracking objects outside tunnels. The proposed methods might not work well in a tunnel because of low illuminance significantly susceptible to tail and warning lights of driving vehicles. The detection performance has rarely been tested against the tunnel environment. This study investigated a feasibility of object detection and tracking in an actual tunnel environment by utilizing YOLOv3 and Kernelized Correlation Filter. We tested 40 actual video clips to differentiate pedestrians and motorcycles to evaluate the performance of our algorithm. The experimental results showed significant difference in detection between pedestrians and motorcycles without false positive rates. Our findings are expected to provide a stepping stone of developing efficient detection algorithms suitable for tunnel environment and encouraging other researchers to glean reliable tracking data for smarter and safer City.

• Smart Media Journal
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• v.11 no.5
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• pp.9-16
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• 2022

Recently, agricultural sites are automating into digital agricultural smart farms by applying technologies such as big data and Internet of Things (IoT). These smart farms aim to increase production and improve crop quality by measuring the environment of crops, investigating and processing data. Production prediction is an important study in smart farm digital agriculture, which is a high-tech agriculture, and it is necessary to analyze environmental data using big data and further standardized research to manage the quality of growth information data. In this paper, environmental and production data collected from smart farm strawberry farms were analyzed and studied. Based on regression analysis, crop production prediction models were analyzed using Ridge Regression, LightGBM, and XGBoost. Among the three models, the optimal model was XGBoost, and R2 showed 82.5 percent explanatory power. As a result of the study, the correlation between the amount of positive fluid absorption and environmental data was confirmed, and significant results were obtained for the production prediction study. In the future, it is expected to contribute to the prevention of environmental pollution and reduction of sheep through the management of sheep by studying the amount of sheep absorption, such as information on the growing environment of crops and the ingredients of sheep.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.12
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• pp.1563-1570
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• 2018

Internet of Things technology is rapidly becoming a reality in many parts of our lives through various product services, and product development especially in the field of smart home is being actively carried out. Most controllers for controlling various smart home products use smart phone applications. However, smart phone applications are not suitable as smart home controllers, contrary to smart home services that emphasize intelligence and convenience. In order to provide intelligent smart home service, intuitive form of smart home controller is needed, which enables integrated control of smart home device. Therefore, this paper proposes a smart home remote control that can control the Internet devices and services of objects. The proposed smart home remote control provides an environment where users can build a smart home service through the IFTTT(If This Then That) automated service platform.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.2
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• pp.301-308
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• 2017

With the popularization of smart phones and the development of the Internet, many people use smart phones to conduct identity verification procedures. smart phones are easier and faster to authenticate than personal desktop computers. However, as Internet hacking technology and malicious code distribution technology rapidly evolve and attack types become more diverse, authentication methods suitable for mobile environment are required. As authentication methods, there are methods such as possessive-based authentication, knowledge-based authentication, biometric-based authentication, pattern-based authentication, and multi-element authentication. In this paper, we propose a user authentication mechanism that uses collected information as authentication factor using smart phone. Using the proposed authentication mechanism, it is possible to use the smart phone information and environment information of the user as a hidden authentication factor, so that the authentication process can be performed without being exposed to others. We implemented the user authentication system using the proposed authentication mechanism and evaluated the effectiveness based on applicability, convenience, and security.

• Smart Media Journal
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• v.6 no.3
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• pp.41-48
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• 2017

Event detection using social media has been widespread since social network services have been an active communication channel for connecting with others, diffusing news message. Especially, the real-time characteristic of social media has created the opportunity for supporting for real-time applications/systems. Social network such as Twitter is the potential data source to explore useful information by mining messages posted by the user community. This paper proposed a novel system for temporal event detection by analyzing social data. As a result, this information can be used by first responders, decision makers, or news agents to gain insight of the situation. The proposed approach takes advantages of deep learning methods that play core techniques on the main tasks including informative data identifying from a noisy environment and temporal event detection. The former is the responsibility of Convolutional Neural Network model trained from labeled Twitter data. The latter is for event detection supported by Recurrent Neural Network module. We demonstrated our approach and experimental results on the case study of earthquake situations. Our system is more adaptive than other systems used traditional methods since deep learning enables to extract the features of data without spending lots of time constructing feature by hand. This benefit makes our approach adaptive to extend to a new context of practice. Moreover, the proposed system promised to respond to acceptable delay within several minutes that will helpful mean for supporting news channel agents or belief plan in case of disaster events.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.161-166
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• 2014

Using and increasing the smart devices got many changes for social environment. Especially, many researchers have studied application using smart devices for improving the learning performance in education. However, Liberal Arts of Humanities has very difficult to apply to information and communication technology cause of traditional study pattern and unit characteristic. In this paper, we suggest a method to apply the Liberal Arts of Humanities to digital broadcasting and to improve learning performance. For this study, we propose a method to making smart contents and connecting them for Liberal Arts of Humanities. And also, we propose a method for applying them to digital broadcasting in order to proof the learning performance increasing by questionary, and shows the application possibility.