• Smart Media Journal
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• v.6 no.4
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• pp.58-64
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• 2017

Modern society is characterized by rapid increase in world population, aging of the rural population, decrease of cultivation area due to industrialization. The food problem is becoming an important issue with the farmers and becomes rural. Recently, the researches about the field of the smart farm are actively carried out to increase the profit of the rural area. The existing smart farm researches mainly monitor the cultivation environment of the crops in the greenhouse, another way like in the case of poor quality t is being studied that the system to control cultivation environmental factors is automatically activated to keep the cultivation environment of crops in optimum conditions. The researches focus on the crops cultivated indoors, and there are not many studies applied to the cultivation environment of crops grown outside. In this paper, we propose a method to improve the harvestability of poor areas by monitoring the areas with bad harvests by using big data analysis, by precisely predicting the harvest timing of fruit trees growing in orchards. Factors besides for harvesting include fruit color information and fruit weight information We suggest that a harvest correlation factor data collected in real time. It is analyzed using the Apache Spark engine. The Apache Spark engine has excellent performance in real-time data analysis as well as high capacity batch data analysis. User device receiving service supports PC user and smartphone users. A sensing data receiving device purpose Arduino, because it requires only simple processing to receive a sensed data and transmit it to the server. It regulates a harvest time of fruit which produces a good quality fruit, it is needful to determine a poor harvest area or concentrate a bad area. In this paper, we also present an architectural model to determine the bad areas of fruit harvest using strong data analysis.

• Journal of Digital Convergence
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• v.14 no.2
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• pp.141-148
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• 2016

Agricultural machines can be viewed as a very important factor to reduce the workforce and reduce production costs as well as keep up with now days trend caused Labor shortages and the workforce reduction by aging in rural. The latest agricultural machinery has developed into a major agricultural industry to apply and integrate the telecommunication, next-generation batteries, semiconductors, wireless communications, content and high-tech display industry technology with a wide range of applications. In this study, to apply the information and communication technologies on agricultural planters relied on a mechanical method, we designed a quick and sophisticated ICT convergence planters that enable to monitor.

• Journal of Fashion Business
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• v.18 no.5
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• pp.82-98
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• 2014

The influence from the increased income and aging society has amplified the interest in the well-being trend and health. People tend to enjoy sports and outdoor life. The development of smart clothing containing heating function to help maintain body temperature has been actively researched after the mid 2000s. However, the domestic study on heating clothing is severely limited. Practical study on designing heating clothing which can be commercialized is needed. The purpose of this study is to develop a commercialized detachable heating vest design through collaboration with a heating vest manufacturer. The results of this study are as follows: 1) Conducted the interview with manufacturer and a demand survey with consumers in order to develop the heating vest design. 2) Developed heating vest design that reflected the wants in the demand survey and sketched the prototype of detachable heating vest. 3) Made a sample of the heating vest and tested the wearability to illustrate the result of this study. Overall, the wearing test result showed high satisfaction for both gender.

• Korean Journal of Applied Biomechanics
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• v.31 no.4
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• pp.249-258
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• 2021

Objective: The aim of this study was to analyze domestic and foreign studies using virtual reality or metaverse for exercise rehabilitation in order to help the disabled or elderly patients with exercise rehabilitation, and suggest a method for using metaverse for exercise rehabilitation. Method: In this study, after analyzing and discussing various information related to the metaverse and exercise rehabilitation through electronic search of recently published papers, academic journals, books, and internet websites, the exercise rehabilitation plan using the metaverse was proposed. Results: In the case of domestic research, the diversity of virtual reality application technology for the rehabilitation of disabled and elderly patients was not secured, but recently, virtual reality or metaverse-related technologies were developed and specialized in a form suitable for exercise rehabilitation. In the case of overseas studies, it was analyzed that exercise rehabilitation using virtual reality and metaverse games for the rehabilitation of disabled and elderly patients can help improve brain, physical ability, and anti-aging by activating the body and mind. Conclusion: Smart metaverse health care is actively introduced to exercise rehabilitation, metaverse telemedicine business is applied to exercise rehabilitation programs, and digital twin games and exercise rehabilitation programs developed by metaverse related companies take into account the characteristics of disabled and elderly patients. If customized smart metaverse healthcare is used for exercise rehabilitation, it is analyzed that it can lead this field.

• Smart Media Journal
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• v.10 no.2
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• pp.22-29
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• 2021

In the past decade, deep learning has been applied to various medical image analysis tasks. Skeletal bone age estimation is clinically important as it can help prevent age-related illness and pave the way for new anti-aging therapies. Recent research has applied deep learning techniques to the task of bone age assessment and achieved positive results. In this paper, we propose a bone age prediction method using a deep convolutional neural network. Specifically, we first train a classification model that automatically localizes the most discriminative region of an image and crops it from the original image. The regions of interest are then used as input for a regression model to estimate the age of the patient. The experiments are conducted on a whole-body scintigraphy dataset that was collected by Chonnam National University Hwasun Hospital. The experimental results illustrate the potential of our proposed method, which has a mean absolute error of 3.35 years. Our proposed framework can be used as a robust supporting tool for clinicians to prevent age-related diseases.

• The Journal of Korea Robotics Society
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• v.16 no.1
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• pp.49-55
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• 2021

Recently, a smart farm technology is drawing attention as an alternative to the decline of farm labor population problems due to the aging society. Especially, there is an increasing demand for automatic harvesting system that can be commercialized in the market. Pre-harvest crop detection is the most important issue for the harvesting robot system in a real-world environment. In this paper, we proposed a real-time tomato instance tracking algorithm by using deep learning and probability models. In general, It is hard to keep track of the same tomato instance between successive frames, because the tomato growing environment is disturbed by the change of lighting condition and a background clutter without a stochastic approach. Therefore, this work suggests that individual tomato object detection for each frame is conducted by YOLOv3 model, and the continuous instance tracking between frames is performed by Kalman filter and probability model. We have verified the performance of the proposed method, an experiment was shown a good result in real-world test data.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.1
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• pp.89-94
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• 2022

With the recent acceleration of an aging society, the use of wheelchairs is increasing, and wheelchair accidents are also increasing. However, despite this situation, the domestic wheelchair market is lacking in deveolpment of additional functions to prevent wheechair collisions and falls. Therefore, this paper aims to design and implement intelligent smart wheelchairs equipped with functions such as stair wheels and automatic illumination sensor headlights that allow wheelchairs to automatically avoid obstacles, notify interlocking applications when falls are detected. Accordingly, it is expected to increase the convenience of wheelchair users and prevent frequent wheelchair accidents.

• Journal of Smart Tourism
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• v.3 no.2
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• pp.23-36
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• 2023

Due to the phenomenon of aging, a new consumer segment known as the "new-silver generation" is emerging. Unlike the previous silver generation, this generation possesses significant economic power and consuming willingness, attracting attention from consumer goods companies. However, both the new-silver generation and the elderly face challenges in adopting contactless or self-service technologies such as self-order kiosks, resulting in negative reactions. Therefore, this study aims to investigate the attitude and response of the newsilver generation towards kiosks, as well as the factors influencing their resistance to such technology. By applying theoretical perspectives from the innovation resistance model, technostress theory, and the value-based model, this study identifies influencing factors for innovation resistance among the new-silver generation when using contactless technologies implemented in fast-food restaurants. The findings indicate that a lower awareness of new technologies and services corresponds to decreased adoption resistance, while a higher perceived value leads to more positive behaviors and attitudes among the new-silver generation utilizing kiosks at fast-food restaurants.

• Smart Media Journal
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• v.13 no.8
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• pp.49-57
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• 2024

In this paper, we propose an algorithm that can recommend personalized health functional foods considering diseases due to the high interest in health functional foods and the development of machine learning as society enters an aging phase. By applying the KNN algorithm, we presented a foundational framework for a platform for personalized health functional food recommendations through disease analysis, matching techniques of publicly available health functional food information, and national public data. To ensure reliable matching between diseases and health functional foods, we analyzed correlations, assessed the appropriateness and accuracy of variables for enhancing the KNN algorithm, and derived improvement directions for the proposed system through the improvement of learning models and information to be disclosed in the future.

• Journal of Digital Convergence
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• v.11 no.3
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• pp.415-426
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• 2013

Smart work has recently introduced as a way to solve problems such as greenhouse gas emissions, low birth rate and aging as well as to improve productivity. Because of development of ICT infrastructure and the proliferation of smart devices, the mobile office has the most commonly used within types of smart work in Korea. But the adoption of the mobile office in small businesses is only half of that of large corporations. The security issue appears to be one of the biggest obstacles to the introduction of smart work in small businesses. Therefore, the purpose of this study is to analyze the information security factors that should be considered when the mobile office is introduced to small businesses. By analyzing the previous studies, the information security factors of the mobile office are classified 5 groups composed of 24 factors. 5 groups are terminals, applications and platforms, networks, servers and users. According to the survey result using AHP, 'User' was drawn to the most important group, and 'Data Encryption', 'Wireless LAN Control' and 'Terminal Recovery When Leaving' were drawn to the important information security factors of the mobile office among 24 factors.