• International Journal of Computer Science & Network Security
• /
• v.23 no.12
• /
• pp.235-245
• /
• 2023

Smart applications based on the Network of Everything also known as Internet of Everything (IoE) are increasing popularity as network connectivity requires rise further. As a result, there will be a greater need for developing 6G technologies for wireless communications in order to overcome the primary limitations of visible 5G networks. Furthermore, implementing neural networks into 6G will bring remedies for the most complex optimizing networks challenges. Future 6G mobile phone networks must handle huge applications that require data and an increasing amount of users. With a ten-year time skyline from thought to the real world, it is presently time for pondering what 6th era (6G) remote correspondence will be just before 5G application. In this article, we talk about 6G dreams to clear the street for the headway of 6G and then some. We start with the conversation of imaginative 5G organizations and afterward underline the need of exploring 6G. Treating proceeding and impending remote organization improvement in a serious way, we expect 6G to contain three critical components: cell phones super broadband, very The Web of Things (or IoT and falsely clever (artificial intelligence). The 6G project is currently in its early phases, and people everywhere must envision and come up with its conceptualization, realization, implementation, and use cases. To that aim, this article presents an environment for Presented Distributed Artificial Intelligence as-a-Services (DAIaaS) supplying in IoE and 6G applications. The case histories and the DAIaaS architecture have been evaluated in terms of from end to end latency and bandwidth consumption, use of energy, and cost savings, with suggestion to improve efficiency.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.24 no.3
• /
• pp.69-76
• /
• 2024

This dissertation developed a five-story vertical livestock and fisheries farm (palm tower) model for sustainable food production in cities. It proposes to integrate marine farms, livestock raising, and pesticide-free automated crop farms to efficiently use resources and minimize environmental impact. Based on circular economy principles, the model can recycle the output of each part into resources from the other, increasing the efficiency of the system, utilizing idle space in the city, and promoting job creation and community participation. It can also contribute to reducing the carbon footprint of food production and improving food safety. In addition, the study explores how advanced agricultural technologies can be integrated into urban structures to address global food security challenges. This model presents potential solutions to the food crisis caused by climate change and population growth, and suggests a direction for the development of urban agriculture. Future research should address the technical and policy challenges for practical implementation.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.24 no.3
• /
• pp.49-53
• /
• 2024

Maritime safety is a critical factor in protecting lives from accidents at sea and fostering a safer marine environment. In this study, we developed a TPMS device aimed at enhancing maritime safety, providing technological solutions for detecting accidents at sea and enabling swift responses. The device utilizes a Tube Pressure Monitoring System (TPMS) to detect tube expansion and is designed to collect real-time data and communicate with surrounding devices for rapid responses. Experimental results confirm the effective detection of pressure by TPMS (Tube Pressure Monitoring System) and stable data transmission and reception with the main IoT device. Additionally, a mobile app capable of receiving emergency alert messages and accessing information for rapid responses in emergency situations was developed. The developed device and mobile app encompass technology applicable not only in the maritime safety field but also in various other application areas, with potential for expanded application in real-world scenarios in the future. These results are expected to contribute to enhancing safety in the marine environment.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.24 no.4
• /
• pp.77-82
• /
• 2024

Recent advancements in artificial intelligence (AI) technology have led to an increase in the implementation of AI applications in mobile environments. However, due to the limited resources in mobile devices compared to desktops and servers, there is growing interest in research aimed at efficiently executing AI workloads on mobile platforms. While most studies focus on offloading to edge or cloud solutions to mitigate computing resource constraints, research on the characteristics of file I/O related to storage access in mobile settings remains underexplored. This paper analyzes file I/O traces generated during the execution of deep learning applications in mobile environments and investigates how they differ from traditional mobile workloads. We anticipate that the findings of this study will be utilized to design future smartphone system software more efficiently, considering the file access characteristics of deep learning.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.24 no.4
• /
• pp.107-112
• /
• 2024

One More Pumpkin won the grand prize at the 2023 Dubai International AI Film Festival, and new possibilities were also opened through the International AI and Metaverse Film Festival (GAMFF), which was held for the first time in Korea. Generative works began to stand out in earnest, with 527 diverse works from 42 countries at home and abroad using AI and metaverse technology submitted to this contest. AI is being used in a variety of fields, including the creation and implementation of digital characters through combination with VFX, improving the efficiency of video production, and managing the overall video production process. This contributes to saving human and material resources required for production and significantly improving the quality of produced videos. However, generative AI also has ambiguity in copyright attribution, ethical issues inherent in the learned dataset, and technical limitations that fall short of the level of human emotion and creativity. Accordingly, this study suggests implications at the level of production, screening, and use, as generative AI may have an impact in more areas in the future.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.24 no.4
• /
• pp.113-119
• /
• 2024

In this paper, a model was devised to change the numerical values that affect the game balance by using Chat-GPT for game balancing. Based on the usability of Chat-GPT shown in several studies and cases using Chat-GPT, Chat-GPT is automated to directly adjust detailed and objective in-game numerical values. In this paper, the format of Chat-GPT responses was consistently adjusted so that the numerical values required for game balancing could be obtained directly from the answers. As an experimental method, it was confirmed that four players autonomously designed the game level through five rounds to adjust the balance. These studies suggest the possibility that games can be produced using Chat-GPT in the future.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.18 no.8
• /
• pp.2450-2463
• /
• 2024

Many legacy information systems are currently being clouded. This is due to the advantage of being able to respond flexibly to the changes in user needs and system environment while reducing the initial investment cost of IT infrastructure such as servers and storage. The infrastructure of the information system migrated to the cloud is being integrated through the API connections, while being subdivided by using MSA (Micro Service Architecture) internally. DBMS (Database Management System) is also becoming larger after cloud migration. Scale calculation in most layers of the application architecture can be measured and calculated from auto-scaling perspective, but the method of hardware scale calculation for DBMS has not been established as standardized methodology. If there is an error in hardware scale calculation of DBMS, problems such as poor performance of the information system or excessive auto-scaling may occur. In addition, evaluating hardware size is more crucial because it also affects the financial cost of the migration. CPU is the factor that has the greatest influence on hardware scale calculation of DBMS. Therefore, this paper aims to calculate the conversion factor for CPU scale calculation that will facilitate the cloud migration between heterogeneous DBMS. In order to do that, we utilize the concept and definition of hardware capacity planning and scale calculation in the on-premise information system. The methods to calculate the conversion factor using TPC-H tests are proposed and verified. In the future, further research and testing should be conducted on the size of the segmented CPU and more heterogeneous DBMS to demonstrate the effectiveness of the proposed test model.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.24 no.5
• /
• pp.61-67
• /
• 2024

In recent years, artificial intelligence and deep learning technologies have made significant advances, and the BERT model has been recognized for its excellent contextual understanding in natural language processing based on the transformer architecture. This performance has the potential to take traditional recommendation systems to the next level. In this study, we adopt an approach that combines a collaborative filtering approach with a deep learning model to improve the performance of recommendation systems. Specifically, we implemented a system that uses BERT to analyze the sentiment of user reviews and embed users based on these review sentiments to find and recommend users with similar tastes. In the process, we also utilized Elasticsearch, an open-source search engine, for quick search and retrieval of recommended results. The approach of analyzing users' textual data to increase the accuracy and personalization of recommendations will play an important role in improving the user experience on various online services in the future.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.24 no.5
• /
• pp.147-157
• /
• 2024

This study empirically analyzed the impact of technological innovation on corporate performance and the moderating effect of technology commercialization capability in this relationship. The purpose was to identify the impact of technological innovation activities, divided into process innovation and product innovation, on financial and non-financial performance, and to clarify the role of technology commercialization capability. An online survey was conducted with 300 companies from April to May 2024, and the results were analyzed using SPSS 29.0 and Process macro. The results showed that technological innovation had a positive effect on both non-financial and financial performance of the company. In addition, it was confirmed that the higher the technology commercialization capability, the stronger the impact of technological innovation on non-financial performance. However, technology commercialization capability did not significantly moderate the relationship between technological innovation and financial performance. This study empirically demonstrated the importance of technology commercialization capability in the relationship between technological innovation and corporate performance, and is expected to provide useful implications for establishing corporate technology innovation strategies and developing policies in the future.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.24 no.5
• /
• pp.19-24
• /
• 2024

Global climate change is causing an increase in natural disasters around the world due to long-term temperature increases and changes in rainfall. Among them, forest fires are becoming increasingly large. South Korea experienced an average of 537 forest fires over a 10-year period (2013-2022), burning 3,560 hectares of forest. That's 1,180 soccer fields(approximately 3 hectares) of forest burning every year. This paper proposed an artificial intelligence based wildfire detection method using image and text information. The performance of the proposed method was compared with YOLOv9-C, RT-DETR-Res50, RT-DETR-L, and YOLO-World-S methods for mAP50, mAP75, and FPS, and it was confirmed that the proposed method has higher performance than other methods. The proposed method was demonstrated as a forest fire detection model of the early forest fire detection system in the Gangwon State, and it is planned to be advanced in the direction of fire detection that can include not only forest areas but also urban areas in the future.