• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.5
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• pp.1085-1092
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• 2018

Recently, Internet (IoT) and big data have been utilized in various fields such as medical, military and sports. Korea Nazarene University is a rehabilitation-welfare university with about 300 students with disabilities. This paper proposes a smart campus that provides the optimal path for the calculation of the route and risk avoidance using the BLE beacon and the 3-axis acceleration sensor when the students with disabilities move in the campus both indoors and outdoors. So we can manage the big data and sensor-based IoT technology for students with disabilities.

• Journal of the Society of Disaster Information
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• v.12 no.3
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• pp.249-260
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• 2016

This paper introduces the results of analysis of questionnaries for developing the effective responding method against social disasters by using ICT technologies. Over 200 peoples including 146 citizens and 55 officials and fireman responded on the questionnaries. In analytical results, approximately 87% citizens answered that the current disaster responding system has some problems, and also over 82% citizens is expecting that ICT is available to reduce the social disaster. For the question of necessity and efficiency of ICT implementation, many officials answered that the information of GIS and facilities would be mostly useful information to respond the social disaster.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.830-832
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• 2019

IoT 기술의 도래로 인하여 실생활에 사용되는 사물들에 Sensor가 부착되어 시간마다 Sensor data가 발생하는 세상이 열리게 되었다. 이러한 IoT Device들에 부착되어 있는 sensor를 통하여 수집이 된 data는 방대한 양을 가지기 때문에 Deep Learning에 적용하는데 충분하며 아주 중요한 역할을 한다. 이러한 IoT Device들은 우리의 실제 생활에 아주 가까이 다양한 환경으로 접할 수 있다. 예를 들어 스마트시티, 스마트팩토리, 스마트홈 등이 있다. 이러한 것들은 우리의 일상생활에 편리함과 직결되어 있다. 본 논문에서는 Smart home 환경에서의 Multi Resident Activity Recognition이다. Smart home의 가구에 부착되어 있는 센서에서 발생된 센서데이터를 활용하여 1) Training Similarity Network, 2) Embedding, 3) Clustering, 4) Recognizing 네 단계 프로세스를 거쳐 문제를 해결한다. 그 결과, 우리가 제안한 프로세스를 통하여 차원 축소 효과와 Un-seen data를 효과적으로 처리할수 있게 된다.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.2
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• pp.209-218
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• 2019

This study proposes a new approach to Control the Orientation and position based on obstacle avoidance technology by multi sensors fusion and autonomous travelling control of mobile robot system for implimentation of Smart FA. The important focus is to control mobile robot based on by the multiple sensor module for autonomous travelling and obstacle avoidance of proposed mobile robot system, and the multiple sensor module is consit with sonar sensors, psd sensors, color recognition sensors, and position recognition sensors. Especially, it is proposed two points for the real time implementation of autonomous travelling control of mobile robot in limited manufacturing environments. One is on the development of the travelling trajectory control algorithm which obtain accurate and fast in considering any constraints. such as uncertain nonlinear dynamic effects. The other is on the real time implementation of obstacle avoidance and autonomous travelling control of mobile robot based on multiple sensors. The reliability of this study has been illustrated by the computer simulation and experiments for autonomous travelling control and obstacle avoidance.

• Smart Media Journal
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• v.9 no.4
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• pp.170-175
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• 2020

It is important to select the most appropriate channel for efficient transmission of massive multimedia data between smart devices in wireless sensor network. In the fixed channel method, sensor nodes can restrict usefulness of frequency and may be a major constraint to support frequency at various environments. In this paper, we propose a modified efficient channel search algorithm that determines available channel and tolerance of interference of links between two nodes. From the results of computer simulation, the proposed method shows that the link of channel can be set efficiently than the other methods even if the number of interference links increases and the beacon packet waiting time caused by interference is reduced remarkably.

• Journal of Drive and Control
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• v.20 no.1
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• pp.8-15
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• 2023

With the recent trend of intelligence and automation of construction work, a double-blade road cutter is being developed that automatically enables cutting along the cutting line marked on the road using a vision system. The road cutter can recognize the cutting line through the camera and correct the driving route in real-time, and it detects the load of the cutting blade in real-time to control the driving speed in case of overload to protect workers and cutting blades. In this study, a vision system mounted on a double-blade road cutter was developed. A cutting route recognition technology was developed to stably recognize cutting lines displayed on non-uniform road surfaces, and performance was verified in similar environments. In addition, a vision sensor protection module was developed to prevent foreign substances (dust, water, etc.) generated during cutting from being attached to the camera.

• Journal of Fashion Business
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• v.18 no.4
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• pp.1-14
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• 2014

Currently smart textile market is rapidly expanding and the demand is increasing integration of an electronic fiber circuit. The garments are an attractive platform for wearable device. This is one of the integration techniques, which consists of is the selective introduction of conductive yarns into the fabric through knitting, weaving or embroidering. The aim of this work is to develop a golf bend driven prototype design for an attachable Arduino that can be used to assess elbow motion. The process begins with the development of a wearable device technique that uses conductive yarn and flex sensor for measurement of elbow bending movements. Also this paper describes and discusses resistance value of zigzag embroidery of the conductive yarns on the tensile properties of the fabrics. Furthermore, by forming a circuit using an Arduino and flex sensor the prototype was created with an assistance band for golf posture training. This study provides valuable information to those interested in the future directions of the smart fashion industry.

• Journal of Korea Multimedia Society
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• v.20 no.6
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• pp.927-934
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• 2017

As the technology of drone develops, the use of drone is increasing, In addition, the types of sensors that are inside of smart phones are becoming various and the accuracy is enhancing day by day. Various of researches are being progressed. Therefore, we need to control drone by using smart phone's sensors. In this paper, we propose the most suitable machine learning model that matches the gyro sensor data with drone's moving. First, we classified drone by it's moving of the gyro sensor value of 4 and 8 degree of freedom. After that, we made it to study machine learning. For the method of machine learning, we applied the One-Rule, Neural Network, Decision Tree, and Navie Bayesian. According to the result of experiment that we designated the value from gyro sensor as the attribute, we had the 97.3 percent of highest accuracy that came out from Naive Bayesian method using 2 attributes in 4 degree of freedom. On and the same, in 8 degree of freedom, Naive Bayesian method using 2 attributes showed the highest accuracy of 93.1 percent.

• Proceedings of the Korea Electromagnetic Engineering Society Conference
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• 2003.11a
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• pp.203-207
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• 2003

Due to the inherent nature of the low flying UAV, obstacle detection is a fundamental requirement in the flight path to avoid the collision from obstacles as well as manned aircraft. In this paper, a preliminary sensor requirements of an obstacle detection system for UAV in low-altitude flight are analyzed, and the automated obstacle detection sensor system is proposed assessing both passive and active sensors such as EO camera, IR, Laser radar, microwave and millimeter radar. In addition, TCAS (Traffic Alert and Collision Avoidance System) are reviewed for the collision avoidance of the manned aircraft system. It is suggested that small-sized radar sensor is the best candidate for the smart UAV because an active radar can provide the real-time informations on range and range rate in the all-weather environment. However, an important constraints on small UAV should be resolved in terms of accommodation of the mass, volume, and power allocated in the payload of the UAV system design requirements.

• Current Industrial and Technological Trends in Aerospace
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• v.6 no.1
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• pp.124-134
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• 2008

The rising demand for the high efficiency and high covertness in UAV motivates the miniature design of the high performing mission sensors, or payloads. One of the promising payload sensors, EO/IR sensor has evolved satisfying its demands and became the main stand-alone mission sensor for 200kg-range UAV. One aspect in development of EO/IR sensor concerns lack of specification criterions to represent its performance. Even though the high demand and competition among each manufacturer caused EO/IR features subject to rapid change collateral to new technology, the datasheets maintained the conventional outdated formats which leave some of the major components in ambiguity. Making comparisons or predicting actual performance with such datasheets is hardly worthwhile; yet, they could be important reference guide for the potential customers what to expect for the upcoming EO/IR. According to UAS Roadmap 2007-2032 published by DoD, one of the main potential customers as well as a main investor of EO/IR technology, EO/IR is expected to play key roll in solving urgent problems, such as see and avoid system. This paper will examine the recent representative EO/IR specialized in UAS missions through datasheets to find out current trend and eventually extrapolate the possible future trend.