• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권5호
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• pp.2245-2266
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• 2016

The hop count routing metric is widely used in routing protocols of Wireless Sensor Networks (WSNs) due to its simplicity and effectiveness. With a lower hop count route, fewer transmissions are required to send a packet from the source to the destination. This can improve the throughput of a network because fewer transmissions results in less channel contention and interference. Despite this, the hop count routing metric may not be ideal for mobile scenarios where the topology of a network changes constantly and rapidly. In this paper, we propose to increase route stability in mobile WSNs by discovering paths that are more stable during route discoveries using routing metrics. Two routing metrics were proposed, the true beauty of these routing metrics lies in the fact that they can even be used even without specialized hardware such as GPS and other sensors. We implemented the proposed routing metrics in the AODV routing protocol and found that they are highly effective and outperform other stability-based routing metrics and the hop count routing metric.

• 한국위성정보통신학회논문지
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• 제2권1호
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• pp.48-55
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• 2007

본 논문은 위성항법지상국시스템 개발을 위하여 시스템 요구사항 정의, 시스템 구성, 시스템에 대한 주요 파라미터별 요구사항 도출 및 분석 결과를 기술한 논문이다. 위성항법 지상국 시스템은 항법 위성인 GPS와 Galileo 위성으로부터 항법 신호를 감시하는 신호감시국과 처리된 위성항법 데이터를 갈릴레오 위성으로 송신하는 상향링크국, 신호감시국 및 상향링크국을 구성하는 장비들에 대한 감시 및 제어기능을 수행하는 감시 및 제어시스템으로 이루어진다. 신호감시국은 항법 수신기와 원자시계, 기상정보처리 및 항법데이타 처리를 담당하는 서브시스템으로 구성되며 항법 수신기는 GPS와 Galileo 위성으로부터 항법 신호를 수신할 수 있는 복합 수신기 형태가 된다. 신호감시국은 항법 정보에 대한 보정정보처리을 위해 위성항법 제어센터인 GCC(GNSS Control Center)와 인터페이스 될 수 있어야 한다.

• 제어로봇시스템학회논문지
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• 제17권5호
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• pp.429-435
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• 2011

This paper presents a sensor fusion-based estimation of heading and a Bezier curve-based motion planning for unmanned ground vehicle. For the vehicle to drive itself autonomously and safely, it should estimate its pose with sufficient accuracy in reasonable processing time. The vehicle should also have a path planning algorithm that enables to adapt to various situations on the road, especially at intersections. First, we address a sensor fusion-based estimation of the heading of the vehicle. Based on extended Kalman filter, the algorithm estimates the heading using the GPS, IMU, and wheel encoders considering the reliability of each sensor measurement. Then, we propose a Bezier curve-based path planner that creates several number of path candidates which are described as Bezier curves with adaptive control points, and selects the best path among them that has the maximum probability of passing through waypoints or arriving at target points. Experiments under various outdoor conditions including at intersections, verify the reliability of our algorithm.

• International Journal of Internet, Broadcasting and Communication
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• 제10권3호
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• pp.42-50
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• 2018

The majority of existing falling recognition techniques provide service by recognizing only that the falling occurred. However, it is important to recognize not only the occurrence of falling but also the situation before and after the falling, as well as the location of the falling. In this paper, we design and propose the falling notification service system to recognize and provide service. This system uses the acceleration sensor of the smartphone to recognize the occurrence of a falling and the situation before and after the falling. In order to check the location of falling, GPS sensor data is used in the Google Map API to map to the map. Also, a crosswalk map converted into grid-based coordinates based on the longitude and latitude of the crosswalk is stored, and the locations before and after falling are mapped. In order to reduce the connection speed and server overload for real-time data processing, fog computing and cloud computing are designed to be distributed processing.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2006년도 International Symposium on GPS/GNSS Vol.1
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• pp.251-256
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• 2006

In the work package 'Integrated Positioning' of the research project NAVIO (Pedestrian Navigation Systems in Combined Indoor/Outdoor Environements) we are dealing with the navigation and guidance of visitors of our University. Thereby start points are public transport stops in the surroundings of the Vienna University of Technology and the user of the system should be guided to certain office rooms or persons. For the position determination of the user different location sensors are employed, i.e., for outdoor positioning GPS and dead reckoning sensors such as a digital compass and gyro for heading determination and accelerometers for the determination of the travelled distance as well as a barometric pressure sensor for altitude determination and for indoor areas location determination using WiFi fingerprinting. All sensors and positioning methods are combined and integrated using a Kalman filter approach. Then an optimal estimate of the current location of the user is obtained using the filter. To perform an adequate weighting of the sensors in the stochastic filter model, the sensor characteristics and their performance was investigated in several tests. The tests were performed in different environments either with free satellite visibility or in urban canyons as well as inside of buildings. The tests have shown that it is possible to determine the user's location continuously with the required precision and that the selected sensors provide a good performance and high reliability. Selected tests results and our approach will be presented in the paper.

• 한국자동차공학회논문집
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• 제22권7호
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• pp.107-116
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• 2014

This paper presents camera-based road surface marking detection methods suited to sensor fusion-based positioning system that consists of low-cost GPS (Global Positioning System), INS (Inertial Navigation System), EDM (Extended Digital Map), and vision system. The proposed vision system consists of two parts: lane marking detection and RSM (Road Surface Marking) detection. The lane marking detection provides ROIs (Region of Interest) that are highly likely to contain RSM. The RSM detection generates candidates in the regions and classifies their types. The proposed system focuses on detecting RSM without false detections and performing real time operation. In order to ensure real time operation, the gating varies for lane marking detection and changes detection methods according to the FSM (Finite State Machine) about the driving situation. Also, a single template matching is used to extract features for both lane marking detection and RSM detection, and it is efficiently implemented by horizontal integral image. Further, multiple step verification is performed to minimize false detections.

• 로봇학회논문지
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• 제16권4호
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• pp.306-312
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• 2021

This paper describes localization of autonomous underwater vehicles(AUV), which can be used when some navigation sensor data are an outlier. In that situation, localization through existing navigation algorithms causes problems in long-range localization. Even if an outlier sensor data occurs once, problems of localization will continue. Also, if outlier sensor data is related to azimuth (direction of AUV), it causes bigger problems. Therefore, a parallel localization module, in which different algorithms are performed in a normal and abnormal situation should be designed. Before designing a parallel localization module, it is necessary to study an effective method in the abnormal situation. So, we propose a localization method through machine learning. For this method, a learning model consists of only Fully-Connected and trains through randomly contaminated real sea data. The ground truth of training is displacement between subsequent GPS data. As a result, average error in localization through the learning model is 0.4 times smaller than the average error in localization through the existing navigation algorithm. Through this result, we conclude that it is suitable for a component of the parallel localization module.

• Asian-Australasian Journal of Animal Sciences
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• 제26권12호
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• pp.1717-1725
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• 2013

The objectives of this study were to compare visual observation and an electronic grazing time method and to evaluate the effects of nutritional plans on intake, grazing behavior and horizontal and vertical locomotion of young bulls in a tropical pasture. Thirty-nine Nellore young bulls with an average body weight of $345{\pm}9.3$ kg kept in pasture were used. The experimental treatments consisted of: restricted: animals kept in a plot with a low mass of forage receiving mineral mixture only; control: animals receiving mineral mixture only; HPHC: a high protein and high carbohydrate supplement; HPLC: a high protein and low carbohydrate supplement; LPHC: a low protein and high carbohydrate supplement; LPLC: a low protein and low carbohydrate supplement. GPS collars equipped with activity sensors were used. Information about head position, latitude, longitude and altitude were recorded. Daytime grazing behavioral patterns monitored by a continuous focal animal recording method was compared to behavior estimated by the activity sensor. Feed intake was estimated by a marker method. The Restricted group presented lower (p<0.05) intake of dry matter and TDN. However, difference in dry matter intake was not found (p>0.05) between non-supplemented and supplemented animals. Difference was not found (p>0.05) in daytime grazing time obtained by visual observation or the activity sensor method. The restricted group showed longer (p<0.05) grazing time (9.58 h/d) than other groups, but difference was not found (p>0.05) in the grazing time between Control (8.35 h/d) and supplemented animals (8.03 h/d). The Restricted group presented lower (p<0.05) horizontal locomotion distance (2,168 m/d) in comparison to other groups (2,580.6 m/d). It can be concluded that the use of activity sensor methods can be recommended due to their being similar to visual observation and able to record 24-h/d. While supplements with high carbohydrates reduce pasture intake, they do not change grazing behavior. Moderate supplementation (until 50% of protein requirement and 30% of energy requirement) of beef cattle on tropical pasture has no effect on daily locomotion.

• 한국통신학회논문지
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• 제39C권6호
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• pp.457-465
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• 2014

본 논문에서는 수중음향센서네트워크의 수중 통신 프로토콜 시험을 위해 구축한 해상시험환경을 소개하고 상용 모뎀을 이용하여 실시한 및 매체접속제어기법(Medium Access Control: MAC)의 시험결과를 제시한다. 본 시험에서는 패킷 충돌을 회피하기 위해 기존 지상환경에서 많이 사용되는 반송파감지기반의 충돌회피기법(Carrier Sense Multiple Access/Collision Avoidance: CSMA/CA)을 사용하였으며 수중 통신 프로토콜로서의 가용성을 검증하였다. 시험에 사용된 네트워크 노드는 Benthos사의 상용 수중 모뎀과 ATmega2560 제어보드를 이용하여 구성하였다. 시험의 체계적 관리와 시험과정 관찰을 용이하게 하기 위해 각 노드가 GPS신호를 수신하여 자신의 위치를 파악할 수 있도록 하였으며 라디오주파수(Radio Frequency: RF) 인터페이스를 통해 위치정보 및 수중채널을 통해 송수신되는 패킷의 정보를 지상으로 보고할 수 있도록 했다. CSMA/CA 프로토콜을 수중환경에 적용하기 위해 4-way 핸드셰이킹동작에 사용되는 네 종류의 제어패킷 RTS(Request To Send), CTS(Clear to Send), DATA, ACK(Acknowledgement)을 수중환경에 맞게 설계했다. 시험을 통해 CSMA/CA 프로토콜의 실제 수중환경에서의 가용성을 검증할 수 있었다.

• 한국체육학회지인문사회과학편
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• 제57권6호
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• pp.293-308
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• 2018

본 연구는 알파인 스키와 관련하여 과거부터 최근까지 진행된 운동역학 연구의 동향을 파악하여 향후 운동역학 분야에서 진행되어야 할 연구 방향을 제언하고자 수행하였다. 운동역학 연구 분야에서는 스키 턴의 메커니즘과 스키어의 등급과 기술 수준에 따른 자세 분석, 스키와 눈의 마찰력, 공기저항 등의 연구가 주로 진행되었다. 이후 측정 센서와 컴퓨터 시뮬레이션을 활용한 연구에서는 IMU와 GPS 센서를 활용하여 스키 장비 개발 및 획득 데이터 검증에 연구가 진행되고 있다. 이와 같은 연구동향을 반영하여 추후 알파인 스키 분야에서 진행되어야 할 운동역학 연구에 대한 제언은 다음과 같다. 첫째, 기존 운동역학 분석 범위의 한계를 넘어 스키 전 구간이 분석 가능하고 스포츠 현장에서 간편하게 활용할 수 있는 측정 장비가 개발되어야 한다. 둘째, 측정 센서를 활용하여 획득한 정보의 정확도 향상과 이를 바탕으로 다양한 분석기법에 관한 연구가 지속적으로 진행되어 스포츠 현장에 도움이 될 수 있는 자료가 제공되어야 한다. 셋째, 컴퓨터 시뮬레이션을 활용하여 스키에서 발생하는 부상 메커니즘을 명확히 정립하고 부상을 예방할 수 있는 방안을 모색해야 한다. 넷째, 컴퓨터 시뮬레이션을 활용한 3차원 스키 모델을 개발하여 실제 주행데이터와 비교 검증함으로써 최적화된 스키 궤적 알고리즘 제공이 필요하다.