• Journal of Internet of Things and Convergence
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• v.8 no.6
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• pp.27-33
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• 2022

Sleep is an essential factor for living a healthy life, but most modern people complain of poor sleep. For these people, as the need for a means to simply evaluate and manage the quality of sleep increases, devices that can check the sleep state at home without monitoring by an examiner are being developed. The smart sleep mask, which is the subject of this usability test, provides bio-signal monitoring while sleeping so that you can conveniently measure and manage your sleep state for yourself. The purpose of this study is to evaluate the usability and safety of the smart sleep mask, to find and prevent potential factors related to errors in use that may occur, and to develop the comfort and safety of this product. As a result of the formative evaluation of the sleep mask prototype, it was reported that it was difficult to turn on the power and check the results, and that the sleep mask was not comfortable to wear. Different opinions were presented on the size and weight of the sleeping mask by people in different age groups.

• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.83-92
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• 2023

The purpose of this study is to provide a rational management strategy to improve the management performance of companies through intellectual property activities. Through this study, we aim to explore countermeasures to strengthen competitiveness in a changing global environment. A survey of 200 companies was conducted from September 1 to October 30, 2023. Statistical analysis was conducted using frequency analysis, exploratory factor analysis, reliability analysis, correlation analysis, multiple regression analysis, and difference analysis. The conclusions are as follows. First, the impact of intellectual property activities on management performance was found to be creation and utilization. Second, the impact of management strategies on management performance was found to be differentiation strategy, cost advantage strategy, and concentration strategy. Third, cost advantage strategy has a partial mediation effect on the relationship between creation activities and managerial performance of intellectual property activities. Fourth, the differentiation strategy has a partial mediating effect on the relationship between the creation of intellectual property activities and managerial performance. In addition, differentiation strategy has a full mediating effect on the relationship between the utilization of intellectual property activities and performance. Fifth, concentration strategy has a partial mediating effect on the relationship between intellectual property activity utilization and management performance. Sixth, there is a difference between creation activities, protection activities, utilization activities, cost advantage strategy, differentiation strategy, financial performance, and non-financial performance based on venture certification status. As the importance of intellectual property is increasing in the era of technological hegemony, IoT companies will need to improve their management performance through venture certification and strategies utilizing intellectual property in order to secure future competitiveness. Based on this study, we hope that IoT companies will maximize their performance by implementing efficient strategies that consider IP activities.

• Information Systems Review
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• v.23 no.3
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• pp.201-223
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• 2021

Smart home is an advanced Internet of Things (IoT) service that enhances the convenience of human daily life and improves the quality of life at home. Recently, with the emergence of smart home products and services to which artificial intelligence (AI) technology is applied, interest in smart home is increasing. To gain a competitive edge in the smart home market, companies are providing "personalized service" to users, which is a key service that can promote smart home use. This study investigates the factors affecting the value awareness of personalized service and intention to use smart home. This research focuses on four-dimensional motivated innovativeness (cognitive, functional, hedonic, and social innovativeness) and privacy risk awareness as key factors that influence the value awareness of personalized service of smart home. In particular, this study conducts a comparative analysis between the generation MZ (young people in late teens to 30s), who are showing socially differentiated characteristics, and the generation X and baby boomers in 40s to 50s or older. Based on the analysis results, this study derives the distinctive characteristics of generation MZ that are different from the older generation, and provides academic and practical implications for expanding the use of smart home services.

• Journal of Internet of Things and Convergence
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• v.8 no.6
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• pp.21-26
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• 2022

This study aims to enhance the cultivation of SW·AI basic competencies of middle school students by forming and distributing SW·AI education programs for middle school students who form the basis of their lives. In addition, by planning SW·AI education programs in connection with the regular curriculum, it is intended to serve as a cornerstone for the public education of SW·AI education that will be implemented from 2025. To this end, the concept of SW and AI in middle school was first defined and a plan to link software/artificial intelligence learning factors to the regular curriculum was proposed, and based on this, SW·AI education programs for middle school students were prepared. Based on literature research, the understanding of artificial intelligence technology, the value of data, and the use of artificial intelligence technology in real life were set as SW·AI education contents, and educational programs were organized by linking them with the current middle school curriculum. All SW·AI education was organized in the form of practice rather than theory so that classes could be conducted centered on participants, and the purpose of the course was to cultivate the ability to use artificial intelligence technology in real life based on understanding artificial intelligence technology.

• 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 Internet of Things and Convergence
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• v.9 no.6
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• pp.29-35
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• 2023

Braille can be said to be an essential means used for the visually impaired to communicate or acquire information on visual materials in their lives. However, the rate of interpretation of braille among the visually impaired is insignificant at 5%. As a result, libraries for the visually impaired produce various types of materials that can obtain various information for the visually impaired and also have assistive technology equipment to interpret them. However, the publication rate of Braille books is too low to purchase and interpret Braille books. In addition, the Braille interpretation rate is too low, and the purchase of assistive technology devices is too expensive and slow. Therefore, in this paper, we implemented a system that displays Braille using Arduino to help visually impaired people in addition to the existing methods they use to obtain information. For Braille display, Korean data is transmitted from Python through serial communication between Python and Arduino, and Arduino, which receives the data, compares the Korean data with the data in the array in the program and retrieves the Braille values of the Korean data. Here, the Braille value was expressed by controlling the servo motor perpendicular or horizontal to the body using white and black circles based on the Braille list.

• Journal of Internet of Things and Convergence
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• v.7 no.3
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• pp.9-14
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• 2021

This paper discovers the energy loss factors through the insulation diagnosis of houses or buildings, and proposes directions for energy efficiency improvement. The energy efficiency factor of a building consists of insulation diagnosis, thermal bridge diagnosis, window diagnosis, airtight diagnosis, and equipment diagnosis. Among the residents and facilities in the energy welfare blind spot, an energy efficiency diagnosis was conducted for one senior citizen building located in Naju-si, Jeollanam-do, and energy efficiency diagnosis was conducted after insulation was installed. Energy measurement, diagnosis and analysis were performed using the IoT-based integrated wired/wireless energy diagnosis platform, Energy Finder. As a result of comparison, an overall energy saving rate of 16.38% was achieved. Annual heating energy consumption per unit area decreased from 333.51kWh before construction to 277.35kWh after construction, and annual cooling energy consumption per unit area decreased from 5.51kWh before construction to 5.22kWh after construction. The annual primary energy consumption per unit area decreased from 464.52kWh before construction to 403.69kWh after construction, and the annual energy cost was reduced from 3,063,307.14 won before construction to 2,641,072.49 won after construction. The additional improvement work is needed on the standards affecting energy efficiency other than insulation.

• Smart Media Journal
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• v.8 no.1
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• pp.74-81
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• 2019

Recently, machine learning technology has had a significant impact on society, particularly in the medical, manufacturing, marketing, finance, broadcasting, and agricultural aspects of human lives. In this paper, we study how to apply machine learning techniques to foods, which have the greatest influence on the human survival. In the field of Smart Farm, which integrates the Internet of Things (IoT) technology into agriculture, we focus on optimizing the crop growth environment by monitoring the growth environment in real time. KT Smart Farm Solution 2.0 has adopted machine learning to optimize temperature and humidity in the greenhouse. Most existing smart farm businesses mainly focus on controlling the growth environment and improving productivity. On the other hand, in this study, we are studying how to apply machine learning with respect to harvest time so that we will be able to harvest fruits of the highest quality and ship them at an excellent cost. In order to apply machine learning techniques to the field of smart farms, it is important to acquire abundant voluminous data. Therefore, to apply accurate machine learning technology, it is necessary to continuously collect large data. Therefore, the color, value, internal temperature, and moisture of greenhouse-grown fruits are collected and secured in real time using color, weight, and temperature/humidity sensors. The proposed FPSML provides an architecture that can be used repeatedly for a similar fruit crop. It allows for a more accurate harvest time as massive data is accumulated continuously.

• Land and Housing Review
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• v.14 no.2
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• pp.125-135
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• 2023

Drones are used in various fields, including land survey, transportation, forestry/agriculture, marine, environment, disaster prevention, water resources, cultural assets, and construction, as their industrial importance and market size have increased. In this study, image data for deep learning was collected using a mavic3 drone capturing images at a shooting altitude was 20 m with ×7 magnification. Swin Transformer and UperNet were employed as the backbone and architecture of the deep learning model. About 800 sheets of labeled data were augmented to increase the amount of data. The learning process encompassed three rounds. The Cross-Entropy loss function was used in the first and second learning; the Tversky loss function was used in the third learning. In the future, when the crack detection model is advanced through convergence with the Internet of Things (IoT) through additional research, it will be possible to detect patching or potholes. In addition, it is expected that real-time detection tasks of drones can quickly secure the detection of pavement maintenance sections.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.3
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• pp.461-467
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• 2019

Advances in location-aware and IoT (Internet of Things) technology increase the rapid generation of massive movement data. Knowledge discovery from massive movement data helps us to understand the urban flow and traffic management. This paper proposes a method to analyze frequent origin-destination sequence patterns from irregular spatiotemporal taxi pick-up locations. The proposed method starts by conducting cluster analysis and then run a frequent sequence pattern analysis based on identified clusters as a base unit. The experimental data is Seoul taxi trajectory data between 7 a.m. and 9 a.m. during one week. The experimental results present that significant frequent sequence patterns occur within Gangnam. The significant frequent sequence patterns of different regions are identified between Gangnam and Seoul City Hall area. Further, this study uses administrative boundaries as a base unit. The results based on administrative boundaries fails to detect the frequent sequence patterns between different regions. The proposed method can be applied to decrease not only taxis' empty-loaded rate, but also improve urban flow management.