• Journal of the Korea Society for Simulation
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• v.18 no.4
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• pp.9-20
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• 2009

Navigation system providing route-guidance and traffic information is one of the most widely used driver-support system these days. Most of the navigation system is based on the 2D map paradigm so the information is ed and encoded from the real world. As a result it imposes a cognitive burden to the driver to interpret and translate the ed information to real world information. As a new concept of navigation system, augmented-reality navigation system (AR navigation) is suggested recently. It provides navigational guidance by imposing graphical information on real image captured by camera mounted on a vehicle in real-time. The ultimate goal of navigation system is to assist the driving task with least driving workload whether it is based on the abstracted graphic paradigm or realistic image paradigm. In this paper, we describe the comparative studies on how map navigation and AR navigation affect for driving tasks by experimental research. From the result of this research we obtained a basic knowledge about the two paradigms of navigation systems. On the basis of this knowledge, we are going to find the optimal design of navigation system supporting driving task most effectively, by analyzing characteristics of driving tasks and navigational information from the human-vehicle interface point of view.

• Journal of Korea Multimedia Society
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• v.19 no.12
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• pp.2014-2023
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• 2016

Web presence is one of the key issues for extensive deployment of Internet-of-Things (IoT). An obstacle to overcome for Web presence is relatively low computing power of IoT devices. In this paper, we present implementation of an IoT platform based on Constrained Application Protocol (CoAP) which is a web transfer protocol proposed by Internet Engineering Task Force (IETF) for the low performance IoT devices such as Wireless Sensor Network (WSN) nodes and micro-controllers. To qualify the performance of CoAP-based IoT system for such an application as smart grid, we designed a test platform consisting of Raspberry Pi2, Kmote WSN node and a desktop PC. Using open source softwares, CoAP was implemented on top of the platform. Leveraging the GET command defined at CoAP specification, performance of the system was measured in terms of round-trip time (RTT) from web application to the Kmote sensor node. To investigate abnormal cases among the test results, hop-by-hop delays were measured to analyze resulting data. The average response time of CoAP-based communication except the abnormal data was reduced by 23% smaller than the previous research result.

• Journal of Advanced Navigation Technology
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• v.17 no.2
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• pp.247-254
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• 2013

The task of 3D gesture recognition for controlling equipments is highly challenging due to the propagation of 3D smart TV recently. In this paper, the AdaBoost algorithm is applied to 3D gesture recognition by using Kinect sensor. By tracking time interval trajectory of hand, wrist and arm by Kinect, AdaBoost algorithm is used to train and classify 3D gesture. Experimental results demonstrate that the proposed method can successfully extract trained gestures from continuous hand, wrist and arm motion in real time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.7
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• pp.1208-1213
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• 2006

A micro embedded did the task to be simply the sequent at the past. The necessity of an embedded operating system did not exist in the reason. We satisfy the complication of the system and operating system have been desired for the officer of the process. The necessity of the process of real-time processing increased also with fast response time to users, The porting follows and have been composed of an real-time embedded operating system. We can control the control unit with the sensor to be established in the building, An embedded web sever to use the resource of the at least is appering a networking facility of interaction. In this paper, The web sever to be implemented in a purity software. We draw data for the thing to implement overall demo to the remote through Internet and We put the point even though we organized the frame to control this. we have successfully ported linux on an embedded system, which is based on intel StrongARM SA-1110 processor, then written several network modules of ethernet-based network device.

• Journal of the Korea Computer Industry Society
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• v.7 no.4
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• pp.309-320
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• 2006

The imprecise real-time system provides flexibility in scheduling time-critical tasks. Most scheduling problems of satisfying both 0/1 constraint and timing constraints, while the total error is minimized, are NP-complete when the optional tasks have arbitrary processing times. Liu suggested a reasonable strategy of scheduling tasks with the 0/1 constraint on uniprocessors for minimizing the total error. Song et al suggested a reasonable strategy of scheduling tasks with the 0/1 constraint on multiprocessors for minimizing the total error. But, these algorithms are all off-line algorithms. In the online scheduling, NORA algorithm can find a schedule with the minimum total error for the imprecise online task system. In the NORA algorithm, the EDF strategy is adopted in the optional scheduling.<중략> The algorithm, proposed in this paper, can be applied to some applications efficiently such as radar tracking, image processing, missile control and so on.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.4
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• pp.293-300
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• 2016

The Voice recognition is one of convenient methods to communicate between human and robots. This study proposes a speech recognition method using speech recognizers based on Hidden Markov Model (HMM) with a combination of techniques to enhance a biped robot control. In the past, Artificial Neural Networks (ANN) and Dynamic Time Wrapping (DTW) were used, however, currently they are less commonly applied to speech recognition systems. This Research confirms that the HMM, an accepted high-performance technique, can be successfully employed to model speech signals. High recognition accuracy can be obtained by using HMMs. Apart from speech modeling techniques, multiple feature extraction methods have been studied to find speech stresses caused by emotions and the environment to improve speech recognition rates. The procedure consisted of 2 parts: one is recognizing robot commands using multiple HMM recognizers, and the other is sending recognized commands to control a robot. In this paper, a practical voice recognition system which can recognize a lot of task commands is proposed. The proposed system consists of a general purpose microprocessor and a useful voice recognition processor which can recognize a limited number of voice patterns. By simulation and experiment, it was illustrated the reliability of voice recognition rates for application of the manufacturing process.

• Informatization Policy
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• v.21 no.1
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• pp.35-56
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• 2014

Information and communication technologies(ICT) allow and force people to work anywhere, anytime using remote databases and application systems available in real-time twenty four hours a day and seven days a week. With the real time nature of ICT, individual work is becoming more and more fragmented. Instead of working on a similar task repeatedly, individuals are required to respond to e-mails and inquiries through social networks, work on planning documents, work on presentation documents, work on spreadsheets, input necessary data on company databases, generate necessary reports from the database, run teleconference, etc., all maybe in a day's work. Work fragmentation may impact negatively on productivity as the flow is interrupted, but it may increase the productivity by allowing people to handle multiple tasks in a shorter time period. This study explores the types of work fragmentation and their characteristics. An online survey was administered to collect data about work fragmentation and work characteristics including autonomy, complexity, flexibility, usage of ICT, etc. 300 cases were used in the analysis. Analysis of k-mean cluster indicated four different types of work fragmentation: concentrated, temporally distributed, spatially distributed, and fully fragmented.

• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.2
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• pp.13-25
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• 2017

Recently, the high performance of tactical situation display console and tactical data links are used to integrate the operational situations in accordance with information age and NCW (Network Centric Warfare). The tendency to maximize the efficiency of task execution has been developed by sharing information and the state of the battle quickly through complex and diverse information exchange. Tactical data link is a communication system that shares the platform with core components of weapons systems and battlefield situation between the command and control systems to perform a Network Centric Warfare and provides a wide range of tactical data required for decision-making and implementation.It provides the tactical information such as tactical information such as operational information, the identification of the peer, and the target location in real time or near real time in the battlefield situation, and it is operated for the exchange of mass tactical information between the intellectuals by providing common situation recognition and cooperation with joint operations. In this study, still image management, audio file management, tactical screen recording and playback using the storage and playback, NITF (National Imagery Transmission Format) message received from the displayer integrates the tactical situation in three dimensions according to multiple data link operation to suggest ways to ensure data integrity between the data link processor during the entire operation time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.12
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• pp.1596-1603
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• 2018

Rapidly detecting and warning of fires is necessary for minimizing human injury and property damage. Generally, when fires occur, both the smoke and the flames are generated, so fire detection systems need to detect both the smoke and the flames. However, most fire detection systems only detect flames or smoke and have the disadvantage of slower processing speed due to additional preprocessing task. In this paper, we implemented a fire detection system which predicts the flames and the smoke at the same time by constructing a CNN model that supports multi-labeled classification. Also, the system can monitor the fire status in real time by using Grad-CAM which visualizes the position of classes based on the characteristics of CNN. Also, we tested our proposed system with 13 fire videos and got an average accuracy of 98.73% and 95.77% respectively for the flames and the smoke.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.85-91
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• 2020

Recently, video-taping equipment such as CCTV have been seeing more use for crime prevention and general safety concerns. Since these video-taping equipment operates all throughout the day, the need for security personnel is lessened, and naturally costs incurred from managing such manpower should also decrease. However, technology currently used predominantly lacks self-sufficiency when given the task of searching for a specific object in the recorded video such as a person, and has to be done manually; current security-based video equipment is insufficient in an environment where real-time information retrieval is required. In this paper, we propose a technology that uses the latest deep-learning technology and OpenCV library to quickly search for a specific person in a video; the search is based on the clothing information that is inputted by the user and transmits the result in real time. We implemented our system to automatically recognize specific human objects in real time by using the YOLO library, whilst deep learning technology is used to classify human clothes into top/bottom clothes. Colors are also detected through the OpenCV library which are then all combined to identify the requested object. The system presented in this paper not only accurately and quickly recognizes a person object with a specific clothing, but also has a potential extensibility that can be used for other types of object recognition in a video surveillance system for various purposes.