• IEMEK Journal of Embedded Systems and Applications
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• v.4 no.3
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• pp.139-147
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• 2009

This paper proposed the context awareness reasoning system to provide the personalized services dynamically in a ubiquitous mobile environments. The proposed system is designed to provide the personalized services to mobile users and consists of the context aggregator and the knowledge manager. The context aggregator can collect information from networks through Open API Gateway as well as sensors in a various ubiquitous environment. And it can also extract the place types through the geocoding and the social address domain ontology. The knowledge manager is the core component to provide the personalized services, and consists of activity reasoner, user pattern learner and service recommender to provide the services predict by extracting the optimized service from user situations. Activity reasoner uses the ontology reasoning and user pattern learner learns with previous service usage history and contexts. And to design service recommender easy to flexibly apply in dynamic environments, service recommender recommends service in the only use of current accessible contexts. Finally, we evaluate the learner and recommender of proposed system by simulation.

• IEMEK Journal of Embedded Systems and Applications
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• v.6 no.1
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• pp.16-24
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• 2011

Automotive Radar Systems are currently under development for various applications to increase accuracy and reliability. The target tracking is most important in single or multiple target environments for accuracy. The tracking algorithm provides smoothed and predicted data for target position and velocity(Doppler). To this end, the fixed gain filter(${\alpha}{\beta}$ filter, ${\alpha}{\beta}{\gamma}$ filter) and dynamic filter(Kalman filter, Singer-Kalman filter, etc) are commonly used. Gating is used to decide whether an observation is assigned to an existing track or new track. Gating algorithms are normally based on computing a statistical error distance between an observation and prediction. The data association takes the observation-to-track pairings that satisfied gating and determines which observation-to-track assignment will actually be made. For data association, NNPDA(Nearest Neighbor Probabilistic Data Association) algorithm is proposed. In this paper, we designed a target tracking system developed for an Automotive Radar System. We show the experimental results of the 77GHz FMCW radar sensor on the roads. Four tracking algorithms(${\alpha}{\beta}$ filter, ${\alpha}{\beta}{\gamma}$ filter, 2nd order Kalman filter, Singer-Kalman filter) have been compared and analyzed to evaluate the performance in test scenario.

• KEPCO Journal on Electric Power and Energy
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• v.6 no.4
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• pp.405-411
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• 2020

In this paper, we designed the COS MEMS system for sensing the falling detection and explosive noise of fuse link in COS (Cut Out Switch) installing on the power distribution. This system analyzed the failure characteristics and an instantaneous breakdown of power distribution. Therefore, our system strengths the industrial competence and guaranties the stable power supply. In this paper, we applied BLE (Bluetooth Low Energy) technology which is suitable protocol for low data rate, low power consumption and low-cost sensor applications. We experimented with LSM6DSOX which is system-in-module featuring 3 axis digital accelerometer and gyroscope boosting in high-performance mode and enabling always-on low-power features for an optimal motion for the COS fuse holder. Also, we used the MP34DT05-A for gathering an ultra-compact, low power, omnidirectional, digital MEMS microphone built with a capacitive sensing element and an IC interface. The proposed COS MEMS system is developed based on nRF52 SoC (System on Chip), and contained a 3-axis digital accelerometer, a digital microphone, and a SD card. In this paper of experiment steps, we analyzed the performance of COS MEMS system with gathering the accelerometer raw data and the PDM (Pulse Data Modulation) data of MEMS microphone for broadcasting the failure of COS status.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.127-130
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• 2005

Internal cities such as gray level been enclosed to building forest are paying a lot of efforts and expenses to change to green city that park and street tree get put together. By the example, 'GREEN CITY of PUSAN 21' progress to decorate army facilities like the park, and to plant street trees in several places of city plan in Pusan. And urban environment that big cities of advanced nation are agreeable is making in the large park and road street trees at several places in downtown. Because price of tree for the park is very expensive, tree management system was all-important. In this paper, Motes deliver the sensor information in each tree through radio sensor network by server side. This information can use in state grasping of tree, harmful insects courtesy call etc and this system design was suggested to inform to mode of life administration scholars.

• Journal of IKEEE
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• v.26 no.3
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• pp.364-372
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• 2022

This paper proposes the design and implementation results for human and object classification systems utilizing frequency modulated continuous wave (FMCW) radar sensor. Such a system requires the process of radar sensor signal processing for multi-target detection and the process of deep learning for the classification of human and object. Since deep learning requires such a great amount of computation and data processing, the lightweight process is utmost essential. Therefore, binary neural network (BNN) structure was adopted, operating convolution neural network (CNN) computation in a binary condition. In addition, for the real-time operation, a hardware accelerator was implemented and verified via FPGA platform. Based on performance evaluation and verified results, it is confirmed that the accuracy for multi-target classification of 90.5%, reduced memory usage by 96.87% compared to CNN and the run time of 5ms are achieved.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.256-258
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• 2016

Domestic vehicle demand is growing steadily. In proportion to the increased interest generated by the automobile-related accidents are more frequent. One of the causes of these accidents are caused by vehicle accidents exists tire problems. Users check tire wear with their naked eyes or check the tread and the wear indicator by using a coin. However, such visual judgment cannot be precise and make it possible to identify the time for tire replacement. Therefore, by utilizing visual and objective data rather than incorrect decisions through objective data, we designed a system that accurately and can easily tell whether the tire condition and replacement of the driver.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.4
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• pp.79-87
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• 2014

In this paper, we implemented the HearCAM platform with Raspberry PI B+ model which is an open source platform. Raspberry PI B+ model consists of dual step-down (buck) power supply with polarity protection circuit and hot-swap protection, Broadcom SoC BCM2835 running at 700MHz, 512MB RAM solered on top of the Broadcom chip, and PI camera serial connector. In this paper, we used the Google speech recognition engine for recognizing the voice characteristics, and implemented the pattern matching with OpenCV software, and extended the functionality of speech ability with SVOX TTS(Text-to-speech) as the matching result talking to the microphone of users. And therefore we implemented the functions of the HearCAM for identifying the voice and pattern characteristics of target image scanning with PI camera with gathering the temperature sensor data under IoT environment. we implemented the speech recognition, pattern matching, and temperature sensor data logging with Wi-Fi wireless communication. And then we directly designed and made the shape of HearCAM with 3D printing technology.

• The Journal of the Korea Contents Association
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• v.9 no.2
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• pp.88-96
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• 2009

In this paper we suggest the EEF technique to improve the performance of U-Health System. The idea of the EEF technique is that a sensor node sends only the abnormal data of patients to the base node. This technique reduces the amount of data transfer between a base node and sensor nodes, and so the power consumption of sensor nodes will be saved. And also the processing cost of base node will be reduced. In the suggested U-Health System based on EEF technique, electrocardiogram sensors and GPS sensors are used to send the electrocardiogram and position information of patients to a server. The server analyzes the health state of patients from base nodes and sends the information about the patients in the emergent state to the nearest hospital. Through the simulation, we have confirmed the suitability of EEF technique for U-Health System.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.10B
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• pp.883-890
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• 2006

The study of sensor network database is beginning to liven up as we are interested in Ubiquitous Computing technology in hardware, communication, database and so on. Especially, as new smart sensors have capabilities of real-time information gathering and analysis of each sensor node, data processing becomes an important issue in Ubiquitous Computing. In thesis, we have applied TinyDB(query processing system) to carry sensor node with line tracer which can follow the fixed path. After we gathered data around path, we have processed data in TinyDB GUI, gathered data, displayed data on a web server. Also we have a web browser on an embedded board for convenient user interface and implemented touch screen such that users can operate with a finger.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.4B
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• pp.184-191
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• 2008

NanoQplus, which is an embedded operating system for wireless sensor networks (WSNs) and developed by Electronics and Telecommunications Research Institute (ETRI), provides programmer-friendly preemptive multi-threading programming technique, but it has poor network protocol stack, as compared to TinyOS, one of the famous operating systems for WSNs. In this paper, we apply dynamic MANET on-demand routing (DYMO) protocol, which is being standardized in Internet Engineering Task Force (IETF), to NanoQplus. Since DYMO has been proposed for mobile ad-hoc networks (MANETs) and MANETs have less resource restrictions than WSNs, the basic DYMO protocol cannot be applied to WSNs without modifications. Moreover, coherence with MAC protocol should be considered in order to eliminate redundant data between MAC and network layers. Thus, we propose a modified version of the basic DYMO protocol for NanoQplus. The experimental results from a real sensor network test-bed show that the DYMO implementation using NanoQplus works efficiently in WSNs.