• Journal of the Korea Society of Computer and Information
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• v.21 no.6
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• pp.63-69
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• 2016

In this paper, we proposed the location tracking system based on MS-Based/Assisted(Mobile Station-Based and Assisted) location trigger service model with context-awareness for the intelligent location tracking of moving objects. It provides the proper resulting value that matches the context of users through the analysis about the situation of the user, physical environment, computing resource and the existing information on user input. In order to provide real-time data, we proposed the location tracking system which realizes the intelligent information such as the expecting arrival time and passing the specific area of the moving object by adopting the location trigger. So, it derives to minimize the costs of communication for the mobile object tracking applications. The proposed location tracking system based on context-awareness can be used for realtime monitoring, intelligent alarm/action, setting up of the optimized moving path, dynamic adjustment of strategies and policies. So it has the advantage to develop the application system which is aimed at optimization of the object tracking and movement.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.6
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• pp.88-95
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• 2011

An embedded mobile device mostly has lower computation power than a general purpose computer because of its relatively lower system specifications. Consequently, conventional face tracking and face detection methods, requiring complex algorithms for higher recognition rates, are unsuitable in a mobile environment aiming for real time detection. On the other hand, by applying a real-time tracking and detecting algorithm, we would be able to provide a two-way interactive multimedia service between an user and a mobile device thus providing a far better quality of service in comparison to a one-way service. Therefore it is necessary to develop a real-time face and eye tracking technique optimized to a mobile environment. For this reason, in this paper, we proposes a method of tracking horizontal face position of a user on a T-DMB device for enhancing the quality of 3D DMB content. The proposed method uses the orientation of edges to estimate the left and right boundary of the face, and by the color edge information, the horizontal position and size of face is determined finally to decide the horizontal face. The sobel gradient vector is projected vertically and candidates of face boundaries are selected, and we proposed a smoothing method and a peak-detection method for the precise decision. Because general face detection algorithms use multi-scale feature vectors, the detection time is too long on a mobile environment. However the proposed algorithm which uses the single-scale detection method can detect the face more faster than conventional face detection methods.

• Proceedings of the Korea Contents Association Conference
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• 2006.11a
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• pp.430-433
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• 2006

A RFID technology that process information of tag attaching in physical object by a point technology that enable this Ubiquitous computing through radio frequency is noted. One of our most important, location tracking for object in RFID system. With this in mind, proposed EPCglobal network gives the location tracking and location services. but, RFID system has the drawbacks. That is special construction and components be positively necessary for RFID system. The service difficult to integrate other service and it increases costs considerably. This thesis gives location service using RFID based on SIP in hospital.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.12
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• pp.1159-1166
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• 2010

Today, detecting the location of moving object has been traced as various methods in our world. In this paper, we preset the system to improve the estimation accuracy utilizing detail localization using radar sensor based on WSN and situational awareness for a calibration (context aware) database, Rail concept. A variety of existing location tracking method has a problem with receiving of data and accuracy as tracking methodology, and since these located data are the only data to be collected for location tracing, the context aware or monitering as the surrounding environment is limited. So, in this paper, we enhanced the distance aware accuracy using radar sensor utilizing the Doppler effect among the distance measuring method, estimated the location using the Triangulation algorithm. Also, since we composed the environment data(temperature, illuminancem, humidity, noise) to entry of the database, it can be utilized in location-based service according to the later action information inference and positive context decision. In order to verify the validity of the suggested method, we give a few random situation and built test bed of designed node, and over the various test we proved the utilizing the context information through route tracking of moving and data processing.

• The KIPS Transactions:PartD
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• v.12D no.6 s.102
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• pp.905-914
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• 2005

This paper suggests a healthcare home service system based on the distributed object group framework that can not only provide healthcare application services using the information obtained from the physical healthcare sensors and devices, and but also monitor and control these services remotely. The distributed object group framework supports the object group service, the interaction service between object groups and the real-time service in order to execute the healthcare application. Here object group means the unit of logical grouped objects or healthcare sensors and devices for a service. Our suggested system consists of 3 layers. The first layer presents the physical sensors and devices for healthcare, as a physical layer. The second layer lays the distributed object group framework, and the third layer, the upper's one, implements healthcare applications based on lower layers. With healthcare applications providing for this system, we implemented the location tracking service, the health information service and the titrating environment service. Also the integrated executing results of these services can be monitored and controlled via remote desktop systems or PDAs.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.1365-1368
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• 2011

The Kalman Filter is one of the most common techniques of tracking mobile user. Web service is a promising method of reusing programs. Therefore, this paper presents our implementation of Kalman Filter web service. There are three ways of implementing a web service system. Ours is Kalman filter as RPC web service.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.638-640
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• 2016

Recently, Humanity enter the super-connection generation that linking human and things as a result of the development ICT technologies. IoT technology is growing rapidly as a result of IoT technology appearance and development of smart device, technology expansion, the spread of smart sensors, spread diffusion of smart devices, construction of a variety of network. These techniques are applied to those having a mobility is growing importance of network technology. Real-time service and features, such as the accuracy of the data it became important. In order to implement the IoT will need to take into account IP, security, a lot of things such as a service model, but in this paper, want to discuss mobility, for the tracking technology of routing path for efficient service delivery of the host. Therefore, in this paper, the routing path that is currently study examined the tracking technology, we try to refer to routing method of the future of the mobile host.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.4
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• pp.344-365
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• 2009

The performance of a tracking system is greatly increased if multiple types of sensors are combined to achieve the objective of the tracking instead of relying on single type of sensor. To conduct the multi-modal tracking, we have previously developed a multi-modal sensor-based tracking model where acoustic sensors mainly track the objects and visual sensors compensate the tracking errors [1]. In this paper, we find a network synchronization problem appearing in the developed tracking system. The problem is caused by the different location and traffic characteristics of multi-modal sensors and non-synchronized arrival of the captured sensor data at a processing server. To effectively deliver the sensor data, we propose a time-based packet aggregation algorithm where the acoustic sensor data are aggregated based on the sampling time and sent to the server. The delivered acoustic sensor data is then compensated by visual images to correct the tracking errors and such a compensation process improves the tracking accuracy in ideal case. However, in real situations, the tracking improvement from visual compensation can be severely degraded due to the aforementioned network synchronization problem, the impact of which is analyzed by simulations in this paper. To resolve the network synchronization problem, we differentiate the service level of sensor traffic based on Weight Round Robin (WRR) scheduling at the routers. The weighting factor allocated to each queue is calculated by a proposed Delay-based Weight Allocation (DWA) algorithm. From the simulations, we show the traffic differentiation model can mitigate the non-synchronization of sensor data. Finally, we analyze expected traffic behaviors of the tracking system in terms of acoustic sampling interval and visual image size.

• Journal of Information Science Theory and Practice
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• v.1 no.1
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• pp.83-91
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• 2013

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.1211-1212
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• 2008

In this paper, we propose image process modeling as a part of location based surveillance system for unauthorized target recognition and tracking in harbor, airport, military zone. For this, we compress and store background image in lower resolution and perform object extraction and motion tracking by using sobel edge detection and difference picture method between real images and a background image. In addition to, we use Independent Component Analysis Neural Network for moving target recognition. Experiments are performed for object extraction and tracking of moving targets on road by using static camera in 20m height building and it shows the robust results.