• 한국항행학회논문지
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• 제27권6호
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• pp.770-775
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• 2023

최근 디지털 데이터 양의 기하급수적 증가는 데이터 처리 시스템의 중요성을 부각시켰다. 이 연구는 클라우드 컴퓨팅 (CC; cloud computing), 엣지 컴퓨팅 (EC; edge computing), 그리고 UAV (unmanned aerial vehicle) 기반 지능형 에지 컴퓨팅 (UEC; unmanned aerial vehicle-based intelligent edge computing) 간의 성능을 비교하였으며, 특히 회랑감시와 같은 실시간 대용량 데이터 처리 상황에 초점을 맞추었습니다. UAV 기반 지능형 에지 컴퓨팅은 이동성과 특수 환경에서의 대규모 데이터 처리 및 분석에 높은 효과성을 보인다. 이러한 연구 결과를 바탕으로 각 상황에 맞게 최적화된 시스템 선택 방법론을 제안한다.

• 방송공학회논문지
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• 제25권2호
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• pp.192-199
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• 2020

최근 딥러닝 모델을 기반으로 한 객체 추적 알고리즘의 활용도가 증가하고 있다. 영상에서의 다중 객체의 추적을 위한 시스템은 대표적으로 객체 검출 알고리즘과 객체 추적 알고리즘의 연쇄된 형태로 구성되어있다. 하지만 여러 모듈로 구성된 연쇄 형태의 시스템은 고성능 컴퓨팅 환경을 요구하며 실제 어플리케이션으로의 적용에 제한사항으로 존재한다. 본 논문에서는 위와 같은 객체 검출-추적의 연쇄 형태의 시스템에서 객체 검출 모듈의 연산 관련 프로세스를 조정하여 저성능 컴퓨팅 환경에서도 실시간 동작을 가능하게 하는 방법을 제안한다.

• 한국통신학회논문지
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• 제17권6호
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• pp.613-620
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• 1992

최근, 퍼지 이론에 따른 정보 처리는 여러 분야에서 그 유효성이 기대되어 많은 연구가 진행되고 있다. 그러나, 일반적인 퍼지 제어 시스템에서는 실제 많은 입력변수의 도입에 따른 퍼지 소속 함수간의 연산 및 추론 시간이 크게 증가되므로, 최근 퍼지 연산을 보다 효과적으로 고속, 병렬 처리 할 수 있는 새로운 퍼지 추론 시스템의 구현이 요구되고 있다.따라서, 본 논문에서는 병렬 및 실시간 처리가 가능한 새로운 접근 방법으로 2차원 공간 광 변조기와 디지털 이미지 보드를 이용한 광 퍼지 추론 시스템을 구성하고, 실제 퍼지 에어컨 시스템에 이를 적용한 실험 결과를 통해 새로운 실시간 광 퍼지 추론 시스템의 구현가능성을 제시 하였다.

• Current Optics and Photonics
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• 제2권5호
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• pp.453-459
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• 2018

We have developed a high-performance signal-processing and image-rendering heterogeneous computation system for optical coherence tomography (OCT) on mobile processor. In this paper, we reveal it by demonstrating real-time OCT image processing using a Snapdragon 800 mobile processor, with the introduction of a heterogeneous image visualization architecture (HIVA) to accelerate the signal-processing and image-visualization procedures. HIVA has been designed to maximize the computational performances of a mobile processor by using a native language compiler, which targets mobile processor, to directly access mobile-processor computing resources and the open computing language (OpenCL) for heterogeneous computation. The developed mobile image processing platform requires only 25 ms to produce an OCT image from $512{\times}1024$ OCT data. This is 617 times faster than the naïve approach without HIVA, which requires more than 15 s. The developed platform can produce 40 OCT images per second, to facilitate real-time mobile OCT image visualization. We believe this study would facilitate the development of portable diagnostic image visualization with medical imaging modality, which requires computationally expensive procedures, using a mobile processor.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권10호
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• pp.3275-3298
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• 2022

Cloud-based architectures for precision agriculture are domain-specific controlled and require remote access to process and analyze the collected data over third-party cloud computing platforms. Due to the dynamic changes in agricultural parameters and restrictions in terms of accessing cloud platforms, developing a locally controlled and real-time configured architecture is crucial for efficient water irrigation and farmers management in agricultural fields. Thus, we present a new implementation of an independent sensor-enabled architecture using variety of wireless-based sensors to capture soil moisture level, amount of supplied water, and compute the reference evapotranspiration (ETo). Both parameters of soil moisture content and ETo values was then used to manage the amount of irrigated water in a small-scale agriculture field for 356 days. We collected around 34,200 experimental data samples to evaluate the performance of the architecture under different agriculture parameters and conditions, which have significant influence on realizing real-time monitoring of agricultural fields. In a proof of concept, we provide empirical results that show that our architecture performs favorably against the cloud-based architecture, as evaluated on collected experimental data through different statistical performance models. Experimental results demonstrate that the architecture has potential practical application in a many of farming activities, including water irrigation management and agricultural condition control.

• Journal of Positioning, Navigation, and Timing
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• 제12권1호
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• pp.75-81
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• 2023

In this study, we design an optimized Graphics Processing Unit (GPU)-based GNSS signal processing technique with the goal of designing and implementing a GNSS Software Defined Receiver (SDR) that can operate in real time all-in-view mode under multi-constellation and multi-frequency signal environment. In the proposed structure the correlators of the existing GNSS SDR are processed by the GPU. We designed a memory structure and processing method that can minimize memory access bottlenecks and optimize the GPU memory resource distribution. The designed GNSS SDR can select and operate only the desired GNSS or desired satellite signals by user input. Also, parameters such as the number of quantization bits, sampling rate, and number of signal tracking arms can be selected. The computing capability of the designed GPU-based GNSS SDR was evaluated and it was confirmed that up to 2400 channels can be processed in real time. As a result, the GPU-based GNSS SDR has sufficient performance to operate in real-time all-in-view mode. In future studies, it will be used for more diverse GNSS signal processing and will be applied to multipath effect analysis using more tracking arms.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 B
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• pp.668-670
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• 1999

We have developed a automatic surface inspection system for cold Rolled strips in steel making process for several years. We have experienced the various kinds of surface inspection systems, including linear CCD camera type and the laser type inspection system which was installed in cold rolled strips production lines. But, we did not satisfied with these inspection systems owing to insufficient detection and classification rate, real time processing performance and limited line speed of real production lines. In order to increase detection and computing power, we have used the Dark Field illumination with Infra_Red LED, Bright Field illumination with Xenon Lamp, Parallel Computing Processor with Area typed CCD camera and full software based image processing technique for the ease up_grading and maintenance. In this paper, we introduced the automatic inspection system and real time image processing technique using the Object Detection, Defect Detection, Classification algorithms. As a result of experiment, under the situation of the high speed processed line(max 1000 meter per minute) defect detection is above 90% for all occurred defects in real line, defect name classification rate is about 80% for most frequently occurred 8 defect, and defect grade classification rate is 84% for name classified defect.

• 한국CDE학회논문집
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• 제13권4호
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• pp.265-272
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• 2008

The flow of technology is going to human-oriented direction, from the time when the computer was first invented, to now where new computing environment using mobile and global network are everywhere. On that technology flow, ubiquitous is being suggested as new paradigm of computing environment. Augmented Reality is one of ubiquitous technologies that provide the interactions between human and computer. By adding computer-generated information to real information and their interaction, user can get the improved and more knowledgeable information about real world. The purpose of this paper is to show the possibility of applying vision based augmented reality to maintenance of product system.

• ETRI Journal
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• 제44권2호
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• pp.194-207
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• 2022

In the last decade, substantial progress has been achieved in intelligent traffic control technologies to overcome consistent difficulties of traffic congestion and its adverse effect on smart cities. Edge computing is one such advanced progress facilitating real-time data transmission among vehicles and roadside units to mitigate congestion. An edge computing-based deep reinforcement learning system is demonstrated in this study that appropriately designs a multiobjective reward function for optimizing different objectives. The system seeks to overcome the challenge of evaluating actions with a simple numerical reward. The selection of reward functions has a significant impact on agents' ability to acquire the ideal behavior for managing multiple traffic signals in a large-scale road network. To ascertain effective reward functions, the agent is trained withusing the proximal policy optimization method in several deep neural network models, including the state-of-the-art transformer network. The system is verified using both hypothetical scenarios and real-world traffic maps. The comprehensive simulation outcomes demonstrate the potency of the suggested reward functions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권5호
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• pp.2310-2345
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• 2017

With the emergence of the Internet of Things (IoT) the world is projecting towards a scenario where every object in the world (including humans) acts as a sender and receiver of data and if we were to see that concept mature we would soon be talking of billions more users of the cloud networks. The cloud technology is a very apt alternative to permanent storage when it comes to bulk storage and reporting. It has however shown weaknesses concerning real-time data accessibility and processing. The bandwidth availability of the cloud networks is limited and combined with the highly centralized storage structure and geographical vastness of the network in terms of distance from the end user the cloud just does not seem like a friendly environment for real-time IOT data. This paper aims at highlighting the importance of Flavio Bonomi's idea of Fog Computing which has been glamorized and marketed by Cisco but has not yet been given a proper service architecture that would explain how it would be used in terms of various service models i-e IaaS, PaaS and SaaS, of the Cloud. The main contribution of the paper would be models for IaaS, PaaS and SaaS for Fog environments. The paper would conclude by highlighting the importance of the presented models and giving a consolidated overview of how they would work. It would also calculate the respective latencies for fog and cloud to prove that our models would work. We have used CloudSim and iFogSim to show the effectiveness of the paradigm shift from traditional cloud architecture to our Fog architecture.