• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.18 no.6
• /
• pp.176-190
• /
• 2019

The prevention of pedestrian accidents in crosswalks and intersections is very important. The C-ITS services provide a warning service for preventing accidents between cars and pedestrians. In the current pedestrian collision prevention warning service according to the C-ITS standard, however, it is difficult to provide real-time service because it detects pedestrians from a video-analysis server in the control center and sends service messages through the ITS system. This paper proposes a pedestrian collision-prevention warning system that detects pedestrians in the local field using an edge camera and sends a warning message directly to the driver through a roadside unit. An evaluation showed that the proposed system could deliver the pedestrian collision prevention-warning message to the driver satisfying the delay time within the 300 ms required by the C-ITS standard, even in the worst case.

• Journal of Digital Contents Society
• /
• v.17 no.4
• /
• pp.219-226
• /
• 2016

In our general life, what we recognize information with our human eyes and use it is diverse and massive. But even the current technologies improved by artificial intelligence are exorbitantly deficient comparing to human visual processing ability. Nevertheless, many researchers are trying to get information in everyday life, especially concentrate effort on recognizing information consisted of text. In the fields of recognizing text, to extract the text from the general document is used in some information processing fields, but to extract and recognize the text from real image is deficient too much yet. It is because the real images have many properties like color, size, orientation and something in common. In this paper, we applies an adaptive edge enhanced MSER(Maximally Stable Extremal Regions) to extract the text area in those diverse environments and the scene text, and show that the proposed method is a comparatively nice method with experiments.

• Journal of Internet Computing and Services
• /
• v.25 no.2
• /
• pp.113-122
• /
• 2024

Recently, cutting-edge ICT technologies such as artificial intelligence, blockchain, edge computing, and the Internet of Things have been applied in various fields to create new services and a new digital era. Along with these technological developments, various policies are being implemented in Korea to transform the country from a "Smart City" to a "Platform City". We can create new services and values by linking with the Smart City Integrated Platform and Smart Housing Platform. This paper defines a linkage scenario between a Smart Housing Platform and the Smart 119 Emergency Dispatch Support Service, one of the Smart City Safety Nets. We propose a data transmission protocol and a metadata schema for data exchange between the Smart Housing Platform and the Smart City Integrated Platform to provide the Smart 119 Emergency Dispatch Support Service.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.13 no.6
• /
• pp.470-476
• /
• 2020

In this paper, we present the design of modular replaceable AI server for image deep learning that separates the server from the Edge Device so as to drive the AI block and the method of data transmission and reception. The modular replaceable AI server for image deep learning can reduce the dependency between social robots and edge devices where the robot's platform will be operated to improve drive stability. When a user requests a function from an AI server for interaction with a social robot, modular functions can be used to return only the results. Modular functions in AI servers can be easily maintained and changed by each module by the server manager. Compared to existing server systems, modular replaceable AI servers produce more efficient performance in terms of server maintenance and scale differences in the programs performed. Through this, more diverse image deep learning can be included in robot scenarios that allow human-robot interaction, and more efficient performance can be achieved when applied to AI servers for image deep learning in addition to robot platforms.

• International Journal of Advanced Culture Technology
• /
• v.8 no.1
• /
• pp.120-127
• /
• 2020

The use of digital signage in the public and commercial communication areas has been increasing in recent years. By integrating cutting-edge information technologies such as 5G, artificial intelligence, and the Internet of Things, digital signage continues to break apart from traditional outdoor advertising media. This study identified the problems facing the domestic digital signage industry by exploring and analyzing major issues related to digital signage and derived future development measures. Specifically, online documents were collected based on the digital signage-related keywords created over the past 12 years to conduct big data network analysis, and key topics were derived through visualization of the results. This study has great policy implications in that it excluded biased interpretations based on the viewpoints of companies or the government and, more objectively, suggested the direction of the digital signage industry's development in the domestic media market.

• Journal of the Korean Society of Industry Convergence
• /
• v.18 no.3
• /
• pp.173-180
• /
• 2015

In this paper, we propose a new precise control technology of robotic gripper for assembling and handling of part. When a robot manipulator interacts mechanically with its environment to perform tasks such as assembly or edge-finishing, the end-effector is thereby constrained by the environment. Therefore grasping force control is very important, since it increases safety due to monitoring of contact force. A comparison of various force control architecture is reported. Different force control methods can often be configured to achieve similar results for a given task, and the choice of control algorithm depends strongly on the application or on the characteristics of a particular robot. In the research, the adjustable gripping force can be controlled and improved the accuracy using the artificial intelligence techniques.

• Journal of Engineering Education Research
• /
• v.24 no.6
• /
• pp.79-85
• /
• 2021

In a future society where cutting-edge science technology such as artificial intelligence becomes commonplace, the demand for talented people with basic knowledge of mathematics and science is expected to increase continuously, and the educational infrastructure suitable for the characteristics of future generations is still insufficient. In particular, in the case of students taking convergence courses including practical training, there was a problem in communication with the instructor. In this study, we looked at the current status of distance learning at domestic universities that came suddenly due to the global pandemic of COVID-19. In addition, a case study of the use of technology was conducted to facilitate the interaction between instructors and learners through case analysis of distance classes in convergence subjects. Therefore, this study aims to introduce the case of developing lecture contents for smooth convergence education in a non-face-to-face educational environment targeting the developed AI convergence courses and applying them to the education of enrolled students.

• Electronics and Telecommunications Trends
• /
• v.36 no.1
• /
• pp.22-31
• /
• 2021

In this thesis, we examine the development status of autonomous mobility services using various artificial intelligence algorithms and propose a solution by combining edge and cloud computing to overcome technical difficulties. A fully autonomous vehicle with enhanced safety and ethics can be implemented using the proposed solution. In addition, for the future of 2035, we present a new concept that enables two- and three-dimensional movement via cooperation between ecofriendly, low-noise, and modular fully autonomous vehicles. The zero-error autonomous driving system will safely and conveniently transport people, goods, and services without time and space constraints and contribute to the autonomous mobility services that are free from movement in connection with various mobility.

• Electronics and Telecommunications Trends
• /
• v.36 no.4
• /
• pp.1-12
• /
• 2021

The competition to lead the next generation of mobile technologies, 6G, is underway while the deployment of 5G has not been implemented worldwide. ITU-R plans to develop technical requirements and standards after completing the 6G Vision by 2023. It can be considered too early to have a concrete view of the 6G core network architecture from this timeline. However, major stakeholders have started making their presence felt by publishing their views. From updated analysis on the technology and service trends proposed, we present a list of research directions on 6G core network from several perspectives: distribution of network functions to nearer edge locations; future fixed-mobile convergence, including low earth orbit satellites; highly-precise QoS guarantee; supporting an extremely wide variety of service requirements; AI-native automation and intelligence; and aligning with the evolution of radio access network.

• Journal of Korea Multimedia Society
• /
• v.25 no.10
• /
• pp.1433-1447
• /
• 2022

Recently, as the demand for physical security technology to prevent leakage of technical and business information of companies and public institutions increases, the high tech companies are operating X-ray security checkpoints at building entrances to protect their intellectual property and technology. X-ray security checkpoints are operated to detect cameras and storage media that may store or leak important technologies in the bags of people entering and leaving the building. In this study, we propose an X-ray security checkpoint system that automatically detects a storage medium in an X-ray image using a deep learning based object detection method. The proposed system consists of an edge computing unit and a cloud-computing unit. We employ the RetinaNet for automatic storage media detection in the X-ray security checkpoint images. The proposed approach achieved mAP of 95.92% on private dataset.