• Science of Emotion and Sensibility
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• v.20 no.1
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• pp.105-114
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• 2017

Nowadays, novel and innovative technology including 3D printers, internet of things (IoT), and wearable devices are rapidly emerging. As we must constantly keep up with the most recent trends, words like convergence, multidisciplinarity, and design revolution indeed define society today. Due to the expansion of such diverse technological, industrial, and academic convergence trends, the role of design is becoming evermore essential in development of products as well as creative services. Even the government is pushing towards a 'creative economy' by encouraging ICT convergence to create novel industries as well as advanced jobs. In order to adapt flexibly to such changes in global trends, a solid academic curriculum centered around 'ICT+Design' must be developed. In the current research, we analyzed various literature and benchmarked the major universities both domestic and foreign. Also we utilized a survey-based approach against subjects who are experts or design specialists working in environments related to industry and research. In our proposed integrated ICT+Design educational curriculum, students familiarize themselves with design perspectives and methodology to creatively carry out the course. Moreover, experts from design and ICT came together in an act of 'Radical Collaboration' in which they shared their unique 'Design Thinking' in order to promote understanding and cooperation. Furthermore, industry experts have also taken part as mentors in order to create a workplace-oriented course with various integrated projects. Most importantly, the course was designed so that in addition to research, students can really get hands-on with their ideas in the creativity-integrated workplace.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.8
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• pp.353-358
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• 2017

An electrical power utility, like an electrical power pole, includes various kinds of sensors for smart services. Temperature data is considered one of the important factors that can influence the smart operations of this utility. This study suggests a method for temperature data analysis for deciding the status of the smart electrical power utilities by using Kalman Filter and Ensemble Model. The suggested approach separates the temperature data according to the different positions of the temperature sensors of a utility, then uses Kalman Filter and Ensemble Model to analyse the characteristics of the temperature variation. With detailed processes, method explains the variation between an external temperature factor like weather temperature data and the sensed temperature data, and then, analysis the temperature data from each position of electrical power utilities. In this process, the suggested method uses Kalman Filter to remove error data and the ensemble model to find out mean value of every hour of electrical data. The result and discussion of temperature analysis were described clearly with the analysed results of electrical data. Finally, we were able to check the working condition of the power devices and the range of the temperature data foe each devices, which may help to indicate any causalities with respect to the devices in the utility pole.

• The Journal of Society for e-Business Studies
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• v.23 no.4
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• pp.1-17
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• 2018

Recently, most online firms are trying to provide personalized services based on customer's data. However, customers are reluctant to give their information to online firm because of concerns about data breach. Online firms are seeking to increase their trust by ensuring the protection of personal information for customers through privacy seal (e.g. e-privacy) or data breach insurance. This research examines the effects of privacy assurance(i.e. privacy seal, data breach insurance) on consumer behavior in online environment. An experiment based on the hypothetical scenario was conducted using a between-subjects 2 (type of privacy assurance) + 1 (control) design. We found that both privacy seal and data breach insurance increased perceived privacy trust. In addition, privacy seal has a positive effect on the intention to provide personal information through perceived privacy trust. Finally, in the case of the group with a high (low) disposition to trust, higher perceived privacy trust is formed through privacy seal (data breach insurance). Theoretical and practical implications are discussed.

• The Journal of the Korea Contents Association
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• v.18 no.12
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• pp.140-149
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• 2018

Along with the recent increase in national income, social phenomena such as aging due to a decrease in population and an increase in single households are observed. There are also an increasing number of households raising pets in proportion to aging households and the increase in the number of single households, most of which use animal companions to overcome loneliness and boost domestic vitality. As more and more people consider pets as family members, the size of the domestic pet market is also growing. The growing number of pets in older households and single households is not properly managed by care such as food meals and exercise management for pets. It is necessary to research and develop robots that can monitor animal companions remotely, feed a certain amount of food at regular intervals, and manage their health through exercise. Among pet companions, dog selection is the highest. Therefore, this study identified robot research on driving methods, examples of existing pet care systems, and researched pet care robots using obstacle avoidance algorithms. In order to use the snack pay behavior and obstacle avoidance algorithm of the pet animals by applying IoT and we .oPI technology, it is able to use ultrasonic sensors on the front and has four infrared sensors on the back. However, this study does not reflect the characteristics of other pet animals as a study on pet care robots, and it requires continuous observation and testing.

• Journal of Digital Convergence
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• v.17 no.8
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• pp.123-130
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• 2019

The advent of the full-fledged Internet of Things era will bring together various types of information through Internet of Things devices, and the vast amount of information collected will be generated as new information by the analysis process. To effectively store this generated information, a flexible and scalable cloud computing system is advantageous. Therefore, the main determinants for effective client system acceptance are viewed as motivator factor (economics, efficiency, etc.) and hindrance factor (transitional costs, security issues, etc.) and the purpose of this study is to determine which detailed factors play a major role in making new system acceptance decisions around harm. The factors required to determine the major priorities are defined as the system acceptance determinants from the technical point of view obtained through the literature review, and the questionnaire is prepared based on the factors derived, and the survey is conducted on the experts concerned. In addition, the AHP analysis aims to achieve a final priority by performing a bifurcation between components for measuring a decision unit. Furthermore, the results of this study will serve as an important basis for making decisions based on acceptance (enabling) of technology.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.4
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• pp.257-268
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• 2021

As the variety and scale of facilities increase due to industrialization and urbanization, blind spots for facility safety management have occurred, resulting in numerous casualties.To meet safety and security needs of citizens living in smart cities, we present a procedure for establishing an integrated platform for facility safety management by combining 5G and digital twin technologies. It can be used to perform inspection according to risk factors and aging of facilities. In this paper, the current status of facility management and application directions of new 5G digital twin-based smart city technologies are reviewed and digital twin implementation procedures are presented. Five cities were selected as target areas: Osan, Gwangmyeong, Guri, Uijeongbu, and Anyang. Old and emergency facilities of each local government were selected. A total of 33 digital twin facilities reflecting policy directions of each city were selected. Focusing on facilities determined by each city, the purpose of this study was to define information technology infrastructure elements for the application of the 5G digital twin facility safety management integrated platform, define categories of implementation services, and suggest a concrete integrated platform configuration plan.

• Convergence Security Journal
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• v.22 no.2
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• pp.115-120
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• 2022

This study analyzed the recent trends in the sports environment to which big data and AI technologies, which are representative technologies of the 4th Industrial Revolution, and approached them from the perspective of convergence of big data and AI technologies in the sports field. And the results are as follows. First, it is being used for player and game data analysis and team strategy establishment and operation. Second, by combining big data collected using GPS, wearable equipment, and IoT with artificial intelligence technology, scientific physical training for each player is possible through user individual motion analysis, which helps to improve performance and efficiently manage injuries. Third, with the introduction of an AI-based judgment system, it is being used for judge judgment. Fourth, it is leading the change in marketing and game broadcasting services. The technology of the 4th Industrial Revolution is bringing innovative changes to all industries, and the sports field is also in the process. The combination of big data and AI is expected to play an important role as a key technology in the rapidly changing future in a sports environment where scientific analysis and training determine victory or defeat.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.221-238
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• 2019

Recently, companies and public institutions have been actively introducing chatbot services in the field of customer counseling and response. The introduction of the chatbot service not only brings labor cost savings to companies and organizations, but also enables rapid communication with customers. Advances in data analytics and artificial intelligence are driving the growth of these chatbot services. The current chatbot can understand users' questions and offer the most appropriate answers to questions through machine learning and deep learning. The advancement of chatbot core technologies such as NLP, NLU, and NLG has made it possible to understand words, understand paragraphs, understand meanings, and understand emotions. For this reason, the value of chatbots continues to rise. However, technology-oriented chatbots can be inconsistent with what users want inherently, so chatbots need to be addressed in the area of the user experience, not just in the area of technology. The Fourth Industrial Revolution represents the importance of the User Experience as well as the advancement of artificial intelligence, big data, cloud, and IoT technologies. The development of IT technology and the importance of user experience have provided people with a variety of environments and changed lifestyles. This means that experiences in interactions with people, services(products) and the environment become very important. Therefore, it is time to develop a user needs-based services(products) that can provide new experiences and values to people. This study proposes a chatbot development process based on user needs by applying the design thinking approach, a representative methodology in the field of user experience, to chatbot development. The process proposed in this study consists of four steps. The first step is 'setting up knowledge domain' to set up the chatbot's expertise. Accumulating the information corresponding to the configured domain and deriving the insight is the second step, 'Knowledge accumulation and Insight identification'. The third step is 'Opportunity Development and Prototyping'. It is going to start full-scale development at this stage. Finally, the 'User Feedback' step is to receive feedback from users on the developed prototype. This creates a "user needs-based service (product)" that meets the process's objectives. Beginning with the fact gathering through user observation, Perform the process of abstraction to derive insights and explore opportunities. Next, it is expected to develop a chatbot that meets the user's needs through the process of materializing to structure the desired information and providing the function that fits the user's mental model. In this study, we present the actual construction examples for the domestic cosmetics market to confirm the effectiveness of the proposed process. The reason why it chose the domestic cosmetics market as its case is because it shows strong characteristics of users' experiences, so it can quickly understand responses from users. This study has a theoretical implication in that it proposed a new chatbot development process by incorporating the design thinking methodology into the chatbot development process. This research is different from the existing chatbot development research in that it focuses on user experience, not technology. It also has practical implications in that companies or institutions propose realistic methods that can be applied immediately. In particular, the process proposed in this study can be accessed and utilized by anyone, since 'user needs-based chatbots' can be developed even if they are not experts. This study suggests that further studies are needed because only one field of study was conducted. In addition to the cosmetics market, additional research should be conducted in various fields in which the user experience appears, such as the smart phone and the automotive market. Through this, it will be able to be reborn as a general process necessary for 'development of chatbots centered on user experience, not technology centered'.

• Journal of Internet Computing and Services
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• v.15 no.3
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• pp.45-52
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• 2014

The Ubiquitous-City (U-City) is a smart or intelligent city to satisfy human beings' desire to enjoy IT services with any device, anytime, anywhere. It is a future city model based on Internet of everything or things (IoE or IoT). It includes a lot of video cameras which are networked together. The networked video cameras support a lot of U-City services as one of the main input data together with sensors. They generate huge amount of video information, real big data for the U-City all the time. It is usually required that the U-City manipulates the big data in real-time. And it is not easy at all. Also, many times, it is required that the accumulated video data are analyzed to detect an event or find a figure among them. It requires a lot of computational power and usually takes a lot of time. Currently we can find researches which try to reduce the processing time of the big video data. Cloud computing can be a good solution to address this matter. There are many cloud computing methodologies which can be used to address the matter. MapReduce is an interesting and attractive methodology for it. It has many advantages and is getting popularity in many areas. Video cameras evolve day by day so that the resolution improves sharply. It leads to the exponential growth of the produced data by the networked video cameras. We are coping with real big data when we have to deal with video image data which are produced by the good quality video cameras. A video surveillance system was not useful until we find the cloud computing. But it is now being widely spread in U-Cities since we find some useful methodologies. Video data are unstructured data thus it is not easy to find a good research result of analyzing the data with MapReduce. This paper presents an analyzing system for the video surveillance system, which is a cloud-computing based video data management system. It is easy to deploy, flexible and reliable. It consists of the video manager, the video monitors, the storage for the video images, the storage client and streaming IN component. The "video monitor" for the video images consists of "video translater" and "protocol manager". The "storage" contains MapReduce analyzer. All components were designed according to the functional requirement of video surveillance system. The "streaming IN" component receives the video data from the networked video cameras and delivers them to the "storage client". It also manages the bottleneck of the network to smooth the data stream. The "storage client" receives the video data from the "streaming IN" component and stores them to the storage. It also helps other components to access the storage. The "video monitor" component transfers the video data by smoothly streaming and manages the protocol. The "video translator" sub-component enables users to manage the resolution, the codec and the frame rate of the video image. The "protocol" sub-component manages the Real Time Streaming Protocol (RTSP) and Real Time Messaging Protocol (RTMP). We use Hadoop Distributed File System(HDFS) for the storage of cloud computing. Hadoop stores the data in HDFS and provides the platform that can process data with simple MapReduce programming model. We suggest our own methodology to analyze the video images using MapReduce in this paper. That is, the workflow of video analysis is presented and detailed explanation is given in this paper. The performance evaluation was experiment and we found that our proposed system worked well. The performance evaluation results are presented in this paper with analysis. With our cluster system, we used compressed $1920{\times}1080(FHD)$ resolution video data, H.264 codec and HDFS as video storage. We measured the processing time according to the number of frame per mapper. Tracing the optimal splitting size of input data and the processing time according to the number of node, we found the linearity of the system performance.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.199-230
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• 2021

Innovative new products and services are being launched through the convergence between heterogeneous industries, and social interest and investment in convergence industries such as AI, big data-based future cars, and robots are continuously increasing. However, in the process of commercialization of convergence new products and services, there are many cases where they do not conform to the existing regulatory and legal system, which causes many difficulties in companies launching their products and services into the market. In response to these industrial changes, the current government is promoting the improvement of existing regulatory mechanisms applied to the relevant industry along with the expansion of investment in new industries. This study, in these convergence industry trends, aimed to analysis the existing regulatory system that is an obstacle to market entry of innovative new products and services in order to preemptively predict regulatory issues that will arise in emerging industries. In addition, it was intended to establish a regulatory impact analysis system to evaluate adequacy and prepare improvement measures. The flow of this study is divided into three parts. In the first part, previous studies on regulatory impact analysis and evaluation systems are investigated. This was used as basic data for the development direction of the regulatory impact framework, indicators and items. In the second regulatory impact analysis framework development part, indicators and items are developed based on the previously investigated data, and these are applied to each stage of the framework. In the last part, a case study was presented to solve the regulatory issues faced by actual companies by applying the developed regulatory impact analysis framework. The case study included the autonomous/electric vehicle industry and the Internet of Things (IoT) industry, because it is one of the emerging industries that the Korean government is most interested in recently, and is judged to be most relevant to the realization of an intelligent information society. Specifically, the regulatory impact analysis framework proposed in this study consists of a total of five steps. The first step is to identify the industrial size of the target products and services, related policies, and regulatory issues. In the second stage, regulatory issues are discovered through review of regulatory improvement items for each stage of commercialization (planning, production, commercialization). In the next step, factors related to regulatory compliance costs are derived and costs incurred for existing regulatory compliance are calculated. In the fourth stage, an alternative is prepared by gathering opinions of the relevant industry and experts in the field, and the necessity, validity, and adequacy of the alternative are reviewed. Finally, in the final stage, the adopted alternatives are formulated so that they can be applied to the legislation, and the alternatives are reviewed by legal experts. The implications of this study are summarized as follows. From a theoretical point of view, it is meaningful in that it clearly presents a series of procedures for regulatory impact analysis as a framework. Although previous studies mainly discussed the importance and necessity of regulatory impact analysis, this study presented a systematic framework in consideration of the various factors required for regulatory impact analysis suggested by prior studies. From a practical point of view, this study has significance in that it was applied to actual regulatory issues based on the regulatory impact analysis framework proposed above. The results of this study show that proposals related to regulatory issues were submitted to government departments and finally the current law was revised, suggesting that the framework proposed in this study can be an effective way to resolve regulatory issues. It is expected that the regulatory impact analysis framework proposed in this study will be a meaningful guideline for technology policy researchers and policy makers in the future.