• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.57-65
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• 2021

A hyper-connected intelligence information society is emerging that creates new value by converging IoT, AI, and Bigdata, which are new technologies of the fourth industrial revolution, in all industrial fields. Everything is connected to the network and data is exploding, and artificial intelligence can learn on its own and even intellectual judgment functions are possible. In particular, the Internet of Things provides a new communication environment that can be connected to anything, anytime, anywhere, enabling super-connections where everything is connected. Artificial intelligence technology is implemented so that computers can execute human perceptions, learning, reasoning, and natural language processing. Artificial intelligence is developing advanced technologies such as machine learning, deep learning, natural language processing, voice recognition, and visual recognition, and includes software, machine learning, and cloud technologies specialized in various applications such as safety, medical, defense, finance, and welfare. Through this, it is utilized in various fields throughout the industry to provide human convenience and new values. However, on the contrary, it is time to respond as intelligent and sophisticated cyber threats are increasing and accompanied by potential adverse functions such as securing the technical safety of new technologies. In this paper, we propose a new data modeling method to enable IoT integrated security control by utilizing artificial intelligence technology as a way to solve these adverse functions.

• The Journal of the Convergence on Culture Technology
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• v.8 no.3
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• pp.143-148
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• 2022

The subject of this paper is the practical examples of technoculture that critically thinks network technology, a strong material foundation in the era of data capitalism in the 21st century, and appropriates its socio-cultural metaphor as an artistic potential. In order to analyze its alternatives and the meaning of cultural politics, this paper examines the properties and influence of data capitalism after the 2008 global financial crisis, and the cultural and artistic context formed by its reaction. The first case considered in this paper, Furtherfield's workshop, provided a useful example of how citizens can participate in social change through learning and education in which art and technology are interrelated. The second case, Greek hackerspace HSGR, developed network technology as a tool to overcome the crisis by proposing a new progressive cultural commons due to Greece's financial crisis caused by the global financial crisis and a decrease in the state's creative support. The third case, Paolo Cirio's project, promoted a critical citizenship towards the state and community systems as dominant types of social governance. These technoculture cases can be evaluated as efforts to combine and rediscover progressive political ideology and its artistic realization tradition in the context of cultural politics, paying attention to the possibility of signifying practices of network technology that dominates the contemporary economic system.

• Journal of Broadcast Engineering
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• v.27 no.5
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• pp.654-664
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• 2022

Immersive content overcomes spatial limitations through convergence with extended reality, artificial intelligence, and photogrammetry technology along with interest due to the COVID-19 pandemic, presenting a new paradigm in the content market such as entertainment, media, performances, and exhibitions. However, it can be seen that in order for realistic content to have sustained public interest, it is necessary to study storytelling method that can increase immersion in content rather than technological freshness. Therefore, in this study, we propose a immersive content storytelling method using artificial intelligence and photogrammetry technology. The proposed storytelling method is to create a content story through interaction between interactive virtual beings and participants. In this way, participation can increase content immersion. This study is expected to help content creators in the accelerating immersive content market with a storytelling methodology through virtual existence that utilizes artificial intelligence technology proposed to content creators to help in efficient content creation. In addition, I think that it will contribute to the establishment of a immersive content production pipeline using artificial intelligence and photogrammetry technology in content production.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.10
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• pp.323-332
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• 2022

As various services using AI technology are being developed, much attention is being paid to AI service production. Recently, AI technology is acknowledged as one of ICT services, a lot of research is being conducted for general-purpose AI service production. In this paper, I describe the research results in terms of systems for AI service production, focusing on the distribution and production of machine learning models, which are the final steps of general machine learning development procedures. Three different Ubuntu systems were built, and experiments were conducted on the system, using data from 2017 validation COCO dataset in combination of different AI models (RFCN, SSD-Mobilenet) and different communication methods (gRPC, REST) to request and perform AI services through Tensorflow serving. Through various experiments, it was found that the type of AI model has a greater influence on AI service inference time than AI machine communication method, and in the case of object detection AI service, the number and complexity of objects in the image are more affected than the file size of the image to be detected. In addition, it was confirmed that if the AI service is performed remotely rather than locally, even if it is a machine with good performance, it takes more time to infer the AI service than if it is performed locally. Through the results of this study, it is expected that system design suitable for service goals, AI model development, and efficient AI service production will be possible.

• Journal of Navigation and Port Research
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• v.46 no.6
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• pp.562-569
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• 2022

The alarm monitoring technology applied to existing operating ships manages data items such as temperature and pressure with AMS (Alarm Monitoring System) and provides an alarm to the crew should these sensing data exceed the normal level range. In addition, the maintenance of existing ships follows the Planned Maintenance System (PMS). whereby the sensing data measured from the equipment is monitored and if it surpasses the set range, maintenance is performed through an alarm, or the corresponding part is replaced in advance after being used for a certain period of time regardless of whether the target device has a malfunction or not. To secure the reliability and operational safety of ship engine operation, it is necessary to enable advanced diagnosis and prediction based on real-time condition monitoring data. To do so, comprehensive measurement of actual ship data, creation of a database, and implementation of a condition diagnosis monitoring system for condition-based predictive maintenance of auxiliary equipment and piping must take place. Furthermore, the system should enable management of auxiliary equipment and piping status information based on a responsive web, and be optimized for screen and resolution so that it can be accessed and used by various mobile devices such as smartphones as well as for viewing on a PC on board. This update cost is low, and the management method is easy. In this paper, we propose CBM (Condition Based Management) technology, for autonomous ships. This core technology is used to identify abnormal phenomena through state diagnosis and monitoring of pumps and purifiers among ship auxiliary equipment, and seawater and steam pipes among pipes. It is intended to provide performance diagnosis and failure prediction of ship auxiliary equipment and piping for convergence analysis, and to support preventive maintenance decision-making.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.5
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• pp.157-166
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• 2022

Exercise is necessary for a healthy life, but it is recommended that it be conducted in a non-face-to-face environment in the context of an epidemic such as COVID-19. However, in the existing non-face-to-face exercise content, it is possible to recognize exercise movements, but the process of interpreting and providing feedback information is not automated. Therefore, in this paper, to solve this problem, we propose a method of creating a formalized rule to track the contents of exercise and the motions that constitute it. To make such a rule, first make a rule for the overall exercise content, and then create a tracking rule for the motions that make up the exercise. A motion tracking rule can be created by dividing the motion into steps and defining a key frame pose that divides the steps, and creating a transition rule between states and states represented by the key frame poses. The rules created in this way are premised on the use of posture and motion recognition technology using motion capture equipment, and are used for logical development for automation of application of these technologies. By using the rules proposed in this paper, not only recognizing the motions appearing in the exercise process, but also automating the interpretation of the entire motion process, making it possible to produce more advanced contents such as an artificial intelligence training system. Accordingly, the quality of feedback on the exercise process can be improved.

• Journal of Software Assessment and Valuation
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• v.17 no.2
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• pp.109-116
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• 2021

Traditionally, the engineering field has been dominated by face-to-face education focused on experimental practice, but demand for online learning has soared due to the rapid development of IT technology and Internet communication networks and recent changes in the social environment such as COVID-19. In order for efficient online education to be conducted in the engineering field, where the proportion of experimental practice is relatively high compared to other fields, virtual laboratory practice content that can replace actual experimental practice is very necessary. In this study, we developed a line tracer model and a virtual experimental software to simulate it for efficient online learning of microprocessor applications that are essential not only in the electric and electronic field but also in the overall engineering field where IT convergence takes place. In the developed line tracer model, the user can set various hardware parameter values in the desired form and write the software in assembly language or C language to test the operation on the computer. The developed line tracer virtual experimental software has been used in actual classes to verify its operation, and is expected to be an efficient virtual experimental practice tool in online non-face-to-face classes.

• Journal of Industrial Convergence
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• v.21 no.1
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• pp.67-76
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• 2023

COVID-19, which occurred in 2019, has a strong contagious power, has serious symptoms of infection and after-effects, and death in severe cases depending on the underlying disease and symptoms. As COVID-19 is highly contagious, in Korea, screening clinics have been set up across the country to determine whether or not to be positive for COVID-19 and isolate the infected to prevent the spread of COVID-19. However, there are cases where COVID-19 test applicants flock to screening clinics and cannot receive tests due to longer waiting times, and there is a risk that secondary infections may occur in the atmosphere. In this study, the reservation and notification system can be applied from the existing screening care system to solve spatial constraints, reducing waiting time with screening appointments, and solving population bottlenecks to screening clinics. Taking the COVID-19 pandemic as an experience, we propose a system that can present directions in future pandemic situations. To process real-time data, we use Google's Firebase to use Realtime Database in the cloud environment. Because a real-time database is used, users can check the status of screening clinics in real time through the app, make reservations, and receive notifications about test reservations.

• Journal of Industrial Convergence
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• v.21 no.1
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• pp.187-192
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• 2023

In this study, trends in ICT education were investigated by analyzing the frequency of appearance of keywords related to machine learning and using conversion of iteration correction(CONCOR) techniques. A total of 304 papers from 2018 to the present published in registered sites were searched on Google Scalar using "ICT education" as the keyword, and 60 papers pertaining to ICT education were selected based on a systematic literature review. Subsequently, keywords were extracted based on the title and summary of the paper. For word frequency and indicator data, 49 keywords with high appearance frequency were extracted by analyzing frequency, via the term frequency-inverse document frequency technique in natural language processing, and words with simultaneous appearance frequency. The relationship degree was verified by analyzing the connection structure and centrality of the connection degree between words, and a cluster composed of words with similarity was derived via CONCOR analysis. First, "education," "research," "result," "utilization," and "analysis" were analyzed as main keywords. Second, by analyzing an N-GRAM network graph with "education" as the keyword, "curriculum" and "utilization" were shown to exhibit the highest correlation level. Third, by conducting a cluster analysis with "education" as the keyword, five groups were formed: "curriculum," "programming," "student," "improvement," and "information." These results indicate that practical research necessary for ICT education can be conducted by analyzing ICT education trends and identifying trends.

• Journal of Industrial Convergence
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• v.21 no.4
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• pp.165-170
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• 2023

There are cases where the mobility impaired have difficulty moving from the moment they leave the house. If guardians also do not have time to entrust their families, who are socially disadvantaged, to a shelter, the guardian has no choice but to check directly in order to know the location of the guardian. The AI home care solution was designed to relieve the anxiety and labor of caregivers and to provide convenience for protection facility officials and users. If more facilities distribute and use services free of charge to non-profit foundations and protective facilities, the concern of guardians will be reduced, and the burden of facility officials who have to manage facility users will be reduced. In this paper, we provide emergency notification services to guardians in the event of an emergency as well as location and status alarms for guardians, which are all data related to movement, in consideration of the mobility vulnerable. Furthermore, it is necessary to provide a service function that recommends the optimal route using a navigation function to ease the convenience and burden of facility officials. It is necessary to alleviate anxiety by providing necessary information to the guardian, such as the location of the shuttle used by the mobile weak and the time of getting on and off. In addition, while providing services for free, the goal is to improve the quality of service for facility managers and the quality of service for the mobility weak.