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메타데이터 서비스 환경에서의 PDR을 위한 역동적 맞춤형 광고 제공 기법
윤경로(Kyoungro Yoon),이희경(Hee-Kyung Lee),강정원(Jung-Won Kang),김재곤(Jae-Gon Kim) 한국방송·미디어공학회 2004 방송공학회논문지 Vol.9 No.4
The convergence of metadata service and the PDR with digital storage device enables new services. Among which, providing dynamic commercials make it possible for the commercials stored in the PDR to be a beneficial information source instead of a dull and not-so-interesting time-consuming content. It also improves consumer concentration and makes the commercials more effective. This paper provides list of various functionality provided by dynamic personalized commercials based on metadata and PDR. The proposed information structure supporting these functionality is based on the digital item concept of MPEG-21. This paper also provides brief description on how the proposed information structure can be used to implement the listed functionality of dynamic personalized commercials.
Intelligent Emergency Alarm System based on Multimedia IoT for Smart City
Kim, Shin,Yoon, Kyoungro The Korean Society Of SemiconductorDisplay Technol 2019 반도체디스플레이기술학회지 Vol.18 No.3
These-days technology related to IoT (Internet of Thing) is widely used and there are many types of smart system based IoT like smart health, smart building and so on. In smart health system, it is possible to check someone's health by analyzing data from wearable IoT device like smart watch. Smart building system aims to collect data from sensor such as humidity, temperature, human counter like that and control the building for energy efficiency, security, safety and so forth. Furthermore, smart city system can comprise several smart systems like smart building, smart health, smart mobility, smart energy and etc. In this paper, we propose multimedia IoT based intelligent emergency alarm system for smart city. In existing IoT based smart system, it communicates lightweight data like text data. In the past, due to network's limitations lightweight IoT protocol was proposed for communicating data between things but now network technology develops, problem which is to communicate heavy data is solving. The proposed system obtains video from IP cameras/CCTVs, analyses the video by exploiting AI algorithm for detecting emergencies and prevents them which cause damage or death. If emergency is detected, the proposed system sends warning message that emergency may occur to people or agencies. We built prototype of the intelligent emergency alarm system based on MQTT and assured that the system detected dangerous situation and sent alarm messages. From the test results, it is expected that the system can prevent damages of people, nature and save human life from emergency.
An efficient spatio-temporal index for spatio-temporal query in wireless sensor networks
( Donhee Lee ),( Kyoungro Yoon ) 한국인터넷정보학회 2017 KSII Transactions on Internet and Information Syst Vol.11 No.10
Recent research into wireless sensor network (WSN)-related technology that senses various data has recognized the need for spatio-temporal queries for searching necessary data from wireless sensor nodes. Answers to the queries are transmitted from sensor nodes, and for the efficient transmission of the sensed data to the application server, research on index processing methods that increase accuracy while reducing the energy consumption in the node and minimizing query delays has been conducted extensively. Previous research has emphasized the importance of accuracy and energy efficiency of the sensor node's routing process. In this study, we propose an itinerary-based R-tree (IR-tree) to solve the existing problems of spatial query processing methods such as efficient processing and expansion of the query to the spatio-temporal domain.
UAV환경에서 스테레오 비전을 활용한 딥러닝 기반 시차맵 추정
이예지(Yegi Lee),윤경로(Kyoungro Yoon) 대한전기학회 2020 전기학회논문지 Vol.69 No.5
Recently, UAVs(Unmanned Aerial Vehicles) are used in various industries such as military, transportation, agriculture and reconnaissance. However, it is very likely to cause an accident such as a collision or fall, due to external environmental factors, and research is needed to increase safety. To prevent such risks, UAVs are often equipped with sensors such as laser scanners or cameras. But laser scanners are very heavy and consume high power. Stereo cameras are much lighter and use less power than laser scanners, making them ideal for use in small UAV environments. Therefore, in this paper, we introduce a method for estimating the disparity map using a stereo camera and deep learning without using a LiDAR(Lighting Detection And Ranging). The proposed method constructs semi-supervision based neural network to estimate disparity maps. This algorithm can estimate more precise disparity maps than existing matching algorithms.