• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.31-36
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• 2024

Recently, mobile apps that utilize AI technologies are increasing. In the personal mobile environment, performance degradation may occur during the training phase of large AI workload due to limitations in memory capacity. In this paper, we extract memory reference traces of AI workloads and analyze their characteristics. From this analysis, we observe that AI workloads can cause frequent storage access due to weak temporal locality and irregular popularity bias during memory write operations, which can degrade the performance of mobile devices. Based on this observation, we discuss ways to efficiently manage memory write operations of AI workloads using persistent memory-based swap devices. Through simulation experiments, we show that the system architecture proposed in this paper can improve the I/O time of mobile systems by more than 80%.

• Electronics and Telecommunications Trends
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• v.37 no.4
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• pp.60-69
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• 2022

So far, artificial intelligence (AI)/machine learning (ML) has produced impressive results in speech recognition, computer vision, and natural language processing. AI/ML has recently begun to show promise as a viable means for improving the performance of 5G mobile telecommunication systems. This paper investigates standardization activities in 3GPP and O-RAN Alliance regarding AI/ML applications on mobile telecommunication system. Future trends in AI/ML technologies are also summarized. As an overarching technology in 6G, there appears to be no doubt that AI/ML could contribute to every part of mobile systems, including core, RAN, and air-interface, in terms of performance enhancement, automation, cost reduction, and energy consumption reduction.

• Journal of Information Processing Systems
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• v.16 no.4
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• pp.743-749
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• 2020

Internet of Things (IoT) is a growing technology along with artificial intelligence (AI) technology. Recently, increasing cases of developing knowledge services using information collected from sensor data have been reported. Communication is required to connect the IoT and AI, and 5G mobile networks have been widely spread recently. IoT, AI services, and 5G mobile networks can be configured and used as sensor-mobile edge-server. The sensor does not send data directly to the server. Instead, the sensor sends data to the mobile edge for quick processing. Subsequently, mobile edge enables the immediate processing of data based on AI technology or by sending data to the server for processing. 5G mobile network technology is used for this data transmission. Therefore, this study examines the challenges, opportunities, and solutions used in each type of technology. To this end, this study addresses clustering, Hyperledger Fabric, data, security, machine vision, convolutional neural network, IoT technology, and resource management of 5G mobile networks.

• Proceedings of the Korea Society of Design Studies Conference
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• 2003.05a
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• pp.272-273
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• 2003

• Journal of the Korean Society of Industry Convergence
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• v.26 no.2_1
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• pp.225-230
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• 2023

This research addresses sound command based human tracking problems for autonomous cleaning mobile robot in a networked AI space. To solve the problem, the difference among the traveling times of the sound command to each of three microphones has been used to calculate the distance and orientation of the sound from the cleaning mobile robot, which carries the microphone array. The cross-correlation between two signals has been applied for detecting the time difference between two signals, which provides reliable and precise value of the time difference compared to the conventional methods. To generate the tracking direction to the sound command, fuzzy rules are applied and the results are used to control the cleaning mobile robot in a real-time. Finally the experiment results show that the proposed algorithm works well, even though the mobile robot knows little about the environment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.951-952
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• 2013

국내 양돈분야에서의 AI(Artificial Insemination)센터는 인공수정 기술의 개발과 보급과 관하여서는 중추적인 역할을 수행하고 있다. 그러나 현재 전국AI센터에서 사용하고 있는 정보관리 시스템은 독립적이고 운영체제에 의존적인 형태로 운영되고 있다. 따라서 현재 전국AI센터 정보관리 체계는 실시간으로 정보관리 시스템의 접근제한과 모바일 서비스 등의 분야에서 그 분명한 한계를 가진다. 이에 본 논문에서는 유무선 통합(FMC) AI PigMoS(Pig Monitoring System, PigMoS) 시스템을 제안하고 구현하였다. 본 논문에서 제안한 FMC AI PigMoS 시스템은 이동성, 실시간 정보관리 등을 지원할 수 있도록 인터넷과 모바일에서 운영할 수 있도록 구현 하였다. 구현된 FMC AI PigMoS 시스템은 이동성과 실시간 정보관리 등에 필요한 모듈 중심으로 설계하고 구현하였다. 이는 원거리 소비자들에게 각 AI센터에서 생성된 AI정보를 실시간으로 제공하여 개별AI센터의 경쟁력 향상을 높일 것으로 기대한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.12A
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• pp.1181-1187
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• 2010

This paper proposes a mobile AI (Artificial Intelligence) conducting decision-making in the game through education for intelligent character on the basis of Neural Network. Neural Network is learned through the input/output value of the algorithm which defines the game rule and the problem solving method. The learned character is able to perceive the circumstances and make proper action. In this paper, the mobile AI using Neural Network has been step-by-step designed, and a simple game has been materialized for its functional experiment. In this game, the goal, the character, and obstacles exist on regular 2D space, and the character, evading obstacles, has to move where the goal is. The mobile AI can achieve its goals in changing environment by learning the solution to several problems through the algorithm defined in each experiment. The defined algorithm and Neural Network are designed to make the input/output system the same. As the experimental results, the suggested mobile AI showed that it could perceive the circumstances to conduct action and to complete its mission. If mobile AI learns the defined algorithm even in the game of complex structure, its Neural Network will be able to show proper results even in the changing environment.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.3
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• pp.549-559
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• 2023

As mobile edge computing (MEC) is gaining attention as a core technology of 5G networks, edge AI technology of 5G network environment based on mobile user data is recently being used in various fields. However, as in traditional AI security, there is a possibility of adversarial interference of standard 5G network functions within the core network responsible for edge AI core functions. In addition, research on data poisoning attacks that can occur in the MEC environment of standalone mode defined in 5G standards by 3GPP is currently insufficient compared to existing LTE networks. In this study, we explore the threat model for the MEC environment using NWDAF, a network function that is responsible for the core function of edge AI in 5G, and propose a feature selection method to improve the performance of detecting data poisoning attacks for Leaf NWDAF as some proof of concept. Through the proposed methodology, we achieved a maximum detection rate of 94.9% for Slowloris attack-based data poisoning attacks in NWDAF.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.2
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• pp.199-208
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• 2017

IoT, Cloud, Bigdata, Mobile, AI, and 3D print, which are called as the main axis of the 4th Industrial Revolution, can be predicted to be changed when the technology is applied to the military. Especially, when I think about the purpose of battle, I think that IoT, Cloud, Bigdata, Mobile, and AI will play many role. Therefore, in this paper, Smart Military is defined as the future military that incorporates these five technologies, and the architecture is established and the appropriate information security model is studied. For this purpose, we studied the existing literature related to IoT, Cloud, Bigdata, Mobile, and AI and found common elements and presented the architecture accordingly. The proposed architecture is divided into strategic information security and tactical information security in the Smart Military environment. In the case of vulnerability, the information security is divided into strategic information security and tactical information security. If a protection system is established, it is expected that the optimum information protection can be constructed within an effective budget range.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.701-702
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• 2013

전국 50여개의 AI(Artificial Insemination)센터는 국내 양돈산업 인공수정 기술을 개발하고 보급하는 중추적인 역할을 수행하고 있다. 이에 반해 AI센터의 숫자 규모는 전국적으로 매우 제한되어 있어, AI센터의 운영 및 AI 기술에 대한 정보관리는 각 센터별 독자적인 운영시스템으로 관리되어 상호 정보융합을 통한 양돈산업 발전에 활용되는 사례가 매우 적다. 또한 개별 AI센터에서 관리하고 있는 소비자들의 지역분포도가 매우 폭넓어 실시간으로 수요자에 대한 판매 관리정보를 제공함에 있어 그 한계를 가지고 있다. 이에 본 논문에서는 전국의 AI센터 관리운영에 통합적이고 효율성을 지원할 수 있는 모바일 웹기반 개선된 AI PigMoS(Pig Monitoring System, PigMoS) 시스템을 제안하고 구현하였다. 본 논문에서 제안한 모바일 웹기반 개선된 AI PigMoS 시스템은 이동성, 실시간 정보서비스 등에 해당되는 시스템 모듈을 모바일 웹을 기반으로 구현하여 개별 AI센터에서 운영할 수 있게 하였다. 이에 본 논문에서는 기존의 AI PigMoS 시스템을 개선하여 재구축하였으며, 이동성, 실시간 정보서비스 등이 필요한 모듈을 중심으로 모바일 기능을 설계하고 구현하여, 원거리 소비자들에게 실시간으로 생성된 AI정보를 제공하여 AI센터의 정보관리 효율성과 경쟁력 향상을 높일 것으로 기대한다.