• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.803-806
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• 2010

본 논문에서는 스크린을 터치를 하지 않고 또한 스크린의 영역의 크기에 상관없이 제스처를 이용하여 인터랙션이 가능한 제스쳐 인식 모듈을 이용한 대규모 멀티 인터랙티브 디스플레이 시스템을 제안한다. IR laser를 이용하여 인터랙션 영역을 생성하고 band pass filter를 장착한 적외선 카메라를 이용하여 인터랙션 영역 안의 영상을 획득한다. 획득되어진 영상은 제안하는 영상처리모듈을 이용하여 이진화->블랍-라벨링 과정을 거쳐 잡음을 제거한 후 인터랙션 영역 안에서 이루어지는 인터랙션 좌표를 획득한 후 Packet으로 저장한다. 저장 된 Packet은 네트워크 통신 시스템을 이용하여 Server로 보내어지고 Server에서는 메타포분석모듈을 이용하여 분석하여 결과를 메타포이벤트로 저장한 후 콘텐츠에 보낸다. 콘텐츠에서는 받은 메타포이벤트에 따라서 콘텐츠 결과를 보여 줌으로써 스크린을 터치 하지 않아도 터치 인터랙션이 가능하며 스크린 영역에 제한 없이 많은 사용자가 동시에 사용이 가능한 시스템 사용이 가능하도록 한다. 본 시스템은 향후 보다 다양한 인터랙션과 시스템 크기의 확장으로 보다 많은 사용자가 동시에 사용가능하며 다양한 인터랙션을 사용할 수 있는 인식 디바이스로써 활용이 가능하다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.11a
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• pp.277-279
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• 2020

최근 무선통신기술의 발달로 텍스트나 이미지 등 적은 양의 데이터를 송출하는 것을 넘어 동영상과 같은 많은 양의 데이터 전송이 가능해졌다. 이에 본 논문은 실시간으로 사고의 상황을 효과적으로 구조기관에 전달하기 위해 GPS와 각종 센서를 활용한 GPS 데이터 및 비디오를 실시간으로 전송하는 무선 네트워크 상황 전파 시스템을 제안한다. Raspberry pi module의 카메라와 GPS 데이터는 ffmpeg와 ffserver를 사용하여 서버와 구조기관으로 실시간 송출 및 전송된다. 제안된 시스템은 실제 프로토타입으로 구현되었으며, 실험 결과 제안한 시스템은 즉각적으로 구조기관에 영상 및 GPS 좌표를 송출함으로써 조기에 사고상황을 파악하고 빠른 구조에 이바지함을 보여준다.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1259-1268
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• 2023

This study proposes a throttle and steering control technology using visual sensors based on deep learning's convolutional and recurrent neural networks. It collects camera image and control value data while driving a training track in clockwise and counterclockwise directions, and generates a model to predict throttle and steering through data sampling and preprocessing for efficient learning. Afterward, the model was validated on a test track in a different environment that was not used for training to find the optimal model and compare it with a CNN (Convolutional Neural Network). As a result, we found that the proposed deep learning model has excellent performance.

• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.243-249
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• 2007

In this paper we introduce a system that assists news reporters to easily edit source video anywhere, and transfer the result from a remote site to the station. Presently reporters are bothered to edit source materials, compress and transfer using several separate tools. Moreover such tools have lots of too complicated features to use only for news production. We have integrated file sending and video editing functions together for seamless workflow. News programs usually need promptness in production. For this reason our system is designed to make it possible the one-stop production of news items outside the TV station. Also the system reflects the demands of field workers, that is, easy usage for the beginner and features for speedy news production. One of the most focused is that the reliability of the system is guaranteed in the process of transfer. To achieve this end, we have implemented several error-resilient schemes for unexpected network errors. Our system consists of remote laptop editing terminals and a newsgathering server. DV-format based editing and analog-to-DV converting device are adopted to capture video from not only lightweight DV camcorders but also old-fashioned ENG cameras into laptop computers. We expect that news reporters and cameramen can take terminals anywhere the Internet is available and both editing and sending will be done on the spot. This will help increase the competitive power of our news production.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.5
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• pp.271-279
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• 2014

In this paper, the two design techniques of the embedded system which provides a wireless image observation with temporary ad-hoc network are proposed and developed. The first method is based on the embedded system design technique for a nearly real-time wireless short observation application, having a specific remote monitoring node with a built-in image processing function, and having the maximum rate of 1 fps (frame per second) wireless image transmission capability of a $160{\times}128$size image. The second technique uses the embedded system for a general wireless long observation application, consisting of the main node, the remote monitoring node, and the system controller with built-in image processing function, and the capability of the wireless image transmission rate of 1/3 fps. The proposed system uses the wireless ad-hoc network which is widely accepted as a short range, low power, and bidirectional digital communication, the hardware are consisted of the general developed modules, a small digital camera, and a PC, and the embedded software based upon the Zigbee stack and the user interface software are developed and tested on the implemented module. The wireless environment analysis and the performance results are presented.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.4
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• pp.569-579
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• 2013

Robot control and image processing using a smartphone and Wi-Fi communication is introduced. The robot has a wheel and quadruped mechanism that is transformed according to the environment and is mainly used for drug bottle delivery. The captured image on the camera is transmitted to the smartphone in the form of stream data, and the image data is processed in the smartphone to enable the robot to identify an object and to control the robot itself. A network was constructed so that only image data from the stream data was used, and an image processing scheme to identify the drug bottle and deliver it to a person using a robot arm is also presented. In this study, image processing techniques and algorithms were purely implemented on a smartphone with considerable computational power and multiple functions rather than a computer, which contributes to the intelligence and miniaturization of the robot system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.537-542
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• 2021

This paper improves the possibility of recognizing fast-moving objects through the YOLO (You Only Look Once) deep learning recognition model in an application environment for object recognition in images. The purpose was to study the method of collecting semantic data through processing. In the recognition model, the moving object recognition error was identified as unrecognized because of the difference between the frame rate of the camera and the moving speed of the object and a misrecognition due to the existence of a similar object in an environment adjacent to the object. To minimize the recognition errors by compensating for errors, such as unrecognized and misrecognized objects through the proposed data collection method, and applying vision processing technology for the causes of errors that may occur in images acquired for sports (tennis games) that can represent real similar environments. The effectiveness of effective secondary data collection was improved by research on methods and processing structures. Therefore, by applying the data collection method proposed in this study, ordinary people can collect and manage data to improve their health and athletic performance in the sports and health industry through the simple shooting of a smart-phone camera.

• Journal of Practical Agriculture & Fisheries Research
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• v.24 no.4
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• pp.53-61
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• 2022

Growing agricultural products in greenhouses controlled by creating suitable climatic conditions and root zone of crop has been an important research and application subject. Appropriate environmental conditions in greenhouse are necessary for optimum plant growth improved crop yields. This study aimed to establish web-based remote monitoring system which monitors crops growth environment and status of crop on a real-time basis by applying to greenhouses IT technology connecting greenhouse equipment such as temperature sensors, soil sensors, crop sensors and camera. The measuring items were air temperature, relative humidity, solar radiation, CO₂ concentration, EC and pH of nutrient solution, medium temperature, EC of medium, water content of medium, leaf temperature, sap flow, stem diameter, fruit diameter, etc. The developed greenhouse monitoring system was composed of the network system, the data collecting device with sensors, and cameras. Remote monitoring system was implemented in a server/client environment. Information on greenhouse environment and crops is stored in a database. Items on growth and environment is extracted from stored information, could be compared and analyzed. So, A integrated monitoring system for smart greenhouse would be use in application practice and understanding the environment and crop growth for smart greenhouse management. sap flow, stem diameter and pant-water relations

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.262-269
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• 2020

Recently, many attempts have been made to reduce the time required for payment in various shopping environments. In addition, for the Fourth Industrial Revolution era, artificial intelligence is advancing, and Internet of Things (IoT) devices are becoming more compact and cheaper. So, by integrating these two technologies, access to building an unmanned environment to save people time has become easier. In this paper, we propose a smart shopping cart system based on low-cost IoT equipment and deep-learning object-detection technology. The proposed smart cart system consists of a camera for real-time product detection, an ultrasonic sensor that acts as a trigger, a weight sensor to determine whether a product is put into or taken out of the shopping cart, an application for smartphones that provides a user interface for a virtual shopping cart, and a deep learning server where learned product data are stored. Communication between each module is through Transmission Control Protocol/Internet Protocol, a Hypertext Transmission Protocol network, a You Only Look Once darknet library, and an object detection system used by the server to recognize products. The user can check a list of items put into the smart cart via the smartphone app, and can automatically pay for them. The smart cart system proposed in this paper can be applied to unmanned stores with high cost-effectiveness.

• Korean Security Journal
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• no.46
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• pp.7-30
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• 2016

This study found the strategies for activating the security industry to utilize social network services based on the platform business model. This research was utilized for in-depth interview and IPA analysis. And use it was to check the contents and strategic improvement projects that can actually materialize and direction of the strategy. First, run a priority need area is a private center of community policing related portal development and operation, universal social networking service(SNS) utilizing expanded, professional training, IT-based security content management and operation of IT infrastructure security guards and security professionals up educational content development, online security guards and security professionals-up refresher training program development. Second, the area over the inventory capabilities increase the effectiveness of the security guards was constructed open-type comprehensive public information system. Third, the area needed to be reviewed are the individual security industry experts workers operating information channels, dedicated customer service and expanding the event of a private security guard & security service providers up. Fourth, the effectiveness of the insufficient area are discuss system improvements, the sharing of community policing closed Cameras for proposals for the expanded utilization of social networking services, private development organizations Social Network Service(SNS).