• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.5
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• pp.77-82
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• 2023

Intelligence Home and Home Automation, which attracted attention before Smart Home, caused inconvenience to users by focusing on applying cutting-edge technologies to homes, and failed to popularize them due to lack of unemployment efficiency. However, with the 4th Industrial Revolution, various services using technologies related to big data, artificial intelligence, and the Internet of Things are increasing, and the rate of smart home services that operate, manage, and automate products at home is gradually increasing. In line with this trend, this paper implements a program app that can connect, manipulate, and manage products using MQTT server, Django web framework, and WIFI communication module.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.3
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• pp.701-707
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• 2024

Industry 4.0 has brought about significant changes in the roles of workers through the introduction of innovative technologies. In smart factory environments, workers are required to interact seamlessly with robots and automated systems, often utilizing equipment enhanced by Virtual Reality (VR) and Augmented Reality (AR) technologies. This study aims to systematically analyze recent research literature on monitoring the physical and mental states of workers in Industry 4.0 environments. Relevant literature was collected using the Web of Science database, employing a comprehensive keyword search strategy involving terms related to Industry 4.0 and health monitoring. The initial search yielded 1,708 documents, which were refined to 923 journal articles. The analysis was conducted using VOSviewer, a tool for visualizing bibliometric data. The study identified general trends in the publication years, countries of authors, and research fields. Keywords were clustered into four main areas: 'Industry 4.0', 'Internet of Things', 'Machine Learning', and 'Monitoring'. The findings highlight that research on health monitoring of workers in Industry 4.0 is still emerging, with most studies focusing on using wearable devices to monitor mental and physical stress and risks. This study provides a foundational overview of the current state of research on health monitoring in Industry 4.0, emphasizing the need for continued exploration in this critical area to enhance worker well-being and productivity.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.1-9
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• 2024

As the Internet of Things (IoT) continues to permeate every facet of modern life, the imperative to secure this vast and dynamic frontier becomes increasingly paramount. This presents a comprehensive exploration of the challenges and opportunities inherent in safeguarding the interconnected web of IoT devices. The research critically examines the limitations of current cybersecurity measures through an extensive review of diverse topics, including IoT network performance, smart grid security, and the escalating cyber threats against critical infrastructures. A meticulous analysis of research findings underscores the need for enhanced infrastructure and ongoing research to fortify the cybersecurity mechanisms surrounding IoT objects. We underline the imperative of relentless research efforts to parry the advancing threats and leverage the promise of nascent technologies. Our findings affirm the pivotal influence of robust cybersecurity measures in crafting a resiliently connected ecosystem. The paper underscores the importance of ongoing research to address evolving threats and harness the potential of emerging technologies, reaffirming the central role of cybersecurity in shaping a secure interconnected world. In conclusion, the study emphasizes the dynamic and ever-evolving nature of cybersecurity on the IoT frontier. It unveils a complex landscape of challenges, ranging from network performance intricacies to the security concerns of critical infrastructures.

• Journal of The Korean Association of Information Education
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• v.24 no.4
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• pp.313-325
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• 2020

There is a growing interest and need for the educational use of artificial intelligence as artificial intelligence technologies such as machine learning and deep learning, the core technologies of the intelligent information society, owing to the recent innovative technological advances. Consequently, the Ministry of Education announced the First Information Education Comprehensive Plan for introducing artificial intelligence competence enhancing education into the education field in preparation for the intelligent information society based on artificial intelligence technologies. Therefore, this study collected 416 overseas papers related to the educational use of artificial intelligence from the Web of Science (WoS) in order to explore the potential for using artificial intelligence educationally. This study analyzed the research status and research topic by country, citation counts, network analysis on keywords of the collected data by using the bibliometrix package of R program. Through this, it was possible to identify the research trend on the educational use of artificial intelligence, currently being conducted in foreign countries. It is believed that it will be possible to obtain implications for the topics and directions to be studied in the information education for strengthening artificial intelligence education based on the results of this study.

• Journal of Internet of Things and Convergence
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• v.6 no.3
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• pp.67-73
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• 2020

The research status of endangered amphibians in Korea was mainly studied the life-cycle and distribution status of species from the 1980s to the early 2000s. Although a relatively diverse range of studies have been conducted on mackerels, studies on habitat prediction, analysis, change and management are insufficient. WEB, which provides biota information using location information in Korea, is a site operated by the National Bio Resource Center under the Ministry of Environment, but there is no information on endangered species and general species information has also been found to be very scantily. For this research, we secured a database of location information of Narrow-mouth frog, an endangered species, by combining literature and field research, and established a system by applying new technologies and open-based platform technologies that can be easily accessed by non-technical personnel of IT among IT technologies. The system was divided into administrator functions and user functions to prevent indiscriminate sharing of information through authentication procedures through user membership of users. The established system was authorized to show the distance between the current location and the location of the Narrow-mouth frog. Considering the ecological characteristics of the Narrow-mouth frog, which is an endangered species, a radius of 500m was marked to determine the habitat range. The system is expected to be applied to the legal system to change existing protected areas, etc. and to select new ones. It is estimated that practical reduction measures can be derived by utilizing the development plan for reviewing the natural environment. In addition, the deployed system has the advantage of being able to apply to a wide variety of endangered species by modifying the information entered.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.320-330
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• 2020

Fire is difficult to achieve good performance in image detection using deep learning because of its high irregularity. In particular, there is little data on fire detection in underground utility facilities, which have poor light conditions and many objects similar to fire. These make fire detection challenging and cause low performance of deep learning models. Therefore, this study proposed a fire detection model using deep learning and estimated the performance of the model. The proposed model was designed using a combination of a basic convolutional neural network, Inception block of GoogleNet, and Skip connection of ResNet to optimize the deep learning model for fire detection under underground utility facilities. In addition, a training technique for the model was proposed. To examine the effectiveness of the method, the trained model was applied to fire images, which included fire and non-fire (which can be misunderstood as a fire) objects under the underground facilities or similar conditions, and results were analyzed. Metrics, such as precision and recall from deep learning models of other studies, were compared with those of the proposed model to estimate the model performance qualitatively. The results showed that the proposed model has high precision and recall for fire detection under low light intensity and both low erroneous and missing detection capabilities for things similar to fire.

• Journal of Global Scholars of Marketing Science
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• v.10
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• pp.1-26
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• 2002

The present study examines the role of subjectively perceived factors of the attitude toward web shopping in forming an intention to use a web shopping intention. An integrative research model is presented and tested empirically. It includes the following three aspects of belief in Davis' TAM: perceived usefulness, perceived ease of use, perceived enjoyment. Specially, internet self-efficacy, or the belief in one's capabilities to organize and execute courses of Internet actions required to produce given attainments, is a potentially important factor in efforts to gain more favorable attitude toward web shopping close the digital divide that separates experienced Internet users from novices. Prior research on Internet self-efficacy has been limited to examining specific task performance and narrow behavioral domains rather than overall attainments in relation to general Internet use, and has not yielded evidence of reliability and construct validity. Survey data were collected to develop a reliable operational measure of Internet self-efficacy and to examine its construct validity. Also, much previous research has established that perceived ease of use is an important factor influencing user acceptance and usage behavior of information technologies. However, very little research has been conducted to understand how that perception forms and changes over time. The present study examines that higher internet self-efficacy is more getting favorable web shopping attitude, and web shopping intention as more as usefulness, enjoyment through the internet.

• Journal of Information Management
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• v.41 no.4
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• pp.187-204
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• 2010

This study shows evaluation of how much OASIS meets "the korean web content accessibility guidelines" and analysis of some of the accessibility problems and their solutions in OASIS(Oriental Medicine Advanced Searching Integrated System) which is the only web site that offers papers and project information related to Traditional Medicine in Korea. The evaluation criteria to determine if OASIS is accessible is classified into four sub items; Perceivable - if information and user interface components is presentable to users in ways they can perceive, Operable - if user interface components and navigation are operable, Understandable - if information and the operation of user interface are understandable, Robust - if content is robust enough that it can be interpreted reliably by a wide variety of user agents, including assistive technologies. Based on the measured results, OASIS has just been redesigned and implemented in more accessible and effective way. OASIS that improves web accessibility for the disabled is expected to help them study oriental medicine more easily and conveniently by providing equal access and equal opportunity to use the web.

• Trans-
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• v.14
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• pp.1-33
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• 2023

In the Web 3.0 era, the third generation of web technologies that uses blockchain technology to give creators ownership of data, metaverse is a crucial trend for developing a creator economy. Web 3.0 aims for a value in which content creators are compensated from participation without being dependent on the platform. Blockchain NFT technology is crucial in metaverse, a vital component of Web 3.0, to ensure the ownership of digital assets. Based on the theory that investigates the concept and characteristics of metaverse, this study identifies five features of the metaverse based NFT art ①'Continuity', ②'Presence', ③ 'Concurrency', ④'Economy', ⑤ 'Application of technology'. By focusing on metaverse based NFT art <Hybrid Nature> case study, we analyzed how the concepts and characteristics of the metaverse and NFT art were reflected in the work. This study focuses on the concept of NFT art, which is emerging at the intersection of art, technology and industry, and emphasizes the importance of finding creative, aesthetic, and cultural values rather than the NFT art's potential for financial gain. It is still in its early stage for academic studies to focus on the aesthetic qualities of NFT art. Future academics and researchers can find this study to gain deeper understanding of the traits and artistic, creative aspects of metaverse based NFT art.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.5
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• pp.231-242
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• 2016

In order to meet rapid changes of Web information, it is necessary to extend the current Web technologies to represent both the valid time and location of each fact and knowledge, and reason their relationships. Until recently, many researches on qualitative temporal reasoning have been conducted in laboratory-scale, dealing with small knowledge bases. However, in this paper, we propose the design and implementation of a parallel qualitative temporal reasoner, MRQUTER, which can make reasoning over Web-scale large knowledge bases. This parallel temporal reasoner was built on a Hadoop cluster system using the MapReduce parallel programming framework. It decomposes the entire qualitative temporal reasoning process into several MapReduce jobs such as the encoding and decoding job, the inverse and equal reasoning job, the transitive reasoning job, the refining job, and applies some optimization techniques into each component reasoning job implemented with a pair of Map and Reduce functions. Through experiments using large benchmarking temporal knowledge bases, MRQUTER shows high reasoning performance and scalability.