• Proceedings of the Korean Society of Computer Information Conference
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• 2014.07a
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• pp.357-360
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• 2014

화재 현장에 투입된 소방대원들은 각종 위험한 환경에 장시간 노출된 상태로 활동을 하고 있으며 또한 열과 연기 등으로 인하여 시야 확보가 매우 어렵고 장시간 화재 진압 및 구조 활동으로 인하여 급격한 체력 저하로 야기되는 소방대원의 인명 피해가 발생되고 있다. 그러므로 본 논문에서는 이러한 인명 피해를 막기 위하여 투입된 소방대원의 위치 추적 및 상태 등을 확인하여 만약에 고립된 소방대원이 있을 경우 안전하게 탈출 할 수 있는 실내 측위 및 추적 기술에 대하여 연구한다.

• Journal of Information Technology Services
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• v.9 no.3
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• pp.145-161
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• 2010

Recently, identifying user locations is becoming important as the society evolves into an ubiquitous society with the innovation of information technology. Particularly, many researches on identifying user locations are headed in direction to identify locations of users in the indoors, because a GPS that is widely used to identify the locations of users in the outdoors is inapplicable in the indoors. However, those researches are mostly not useful to general indoor environment because they are performed in a specific environment with specialized or customized devices such as UWB, RFID. Therefore, in this paper we propose a effective method to identify user locations in general indoor environments with wireless local network access points. Our approach enables to identify user location efficiently by measuring signal power of access points around the user and using the FRIIS formula which is used to calculate the distance among the things.

• Journal of Digital Convergence
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• v.11 no.4
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• pp.243-249
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• 2013

In this paper, GPS(Global Positioning System) that can be used outdoors and GPS(Global Positioning System) is not available for indoor Wi-Fi(Wireless Fidelity) using the Android-based location information system has been designed and implemented. Pedestrians in a room in order to estimate the location of the pedestrian's position, regardless of need to obtain the absolute position and relative position, depending on the movement of pedestrians in a row it is necessary to estimate. In order to estimate the initial position of the pedestrian Wi-Fi Fingerprinting was used. Most existing Wi-Fi Fingerprinting position error small WKNN(Weighted K Nearest Neighbor) algorithm shortcoming EWKNN (Enhanced Weighted K Nearest Neighbor) using the algorithm raised the accuracy of the position. And in order to estimate the relative position of the pedestrian, the smart phone is mounted on the IMUInertial Measurement Unit) because the use did not require additional equipment.

• IEIE Transactions on Smart Processing and Computing
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• v.1 no.2
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• pp.106-116
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• 2012

The huge success of location-aware applications has called for the rapid development of an alternative positioning system to the global positioning system (GPS) for indoor localization based on existing technologies, such as 802.11 wireless networks. This paper proposes the Wireless MAC Processor Positioning System (WMPS), which is a localization system running on off-the-shelf 802.11 Access Points and based on the time-of-flight ranging of users' standard terminals. This paper proves through extensive experiments that the propagation delays can be measured with the accuracy required by indoor applications despite the different noise components that can affect the result: latencies of the hardware transreceivers, multipath, ACK jitters and timer quantization. Key to this solution is the choice of the Wireless MAC Processor architecture, which enables a straightforward implementation of the ranging subsystem directly inside the commercial cards without affecting the basic DCF channel access algorithm. In addition to the proposed measurement framework, this study developed a simple and effective localization algorithm that can work without requiring any preliminary calibration or device characterization. Finally, the architecture allows the measurement methodology to be adjusted as a function of the network load or propagation environments at the run time, without requiring any firmware update.

• Journal of Internet Computing and Services
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• v.7 no.3
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• pp.31-39
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• 2006

Ubiquitous and pervasive environment presents opportunities for a rich set of location aware applications such as car navigation and intelligent robots, interactive virtual games, logistics service, asset tracking etc. Typical indoor location systems require better accuracy than what current outdoor location systems provide, Outdoor location technologies such as GPS have poor indoor performance because of the harsh nature of indoor environments, In this paper we present a novel reducing interference location system that is particularly well suited to support context aware computing. The system, called EEM (Enhance Envelop Method) alms to combine the advantages of real time tracking systems that implement distributed environment with the suitability of infrastructure sensor network.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.5
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• pp.433-439
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• 2010

This paper proposes a beacon color code scheduling algorithm for the localization of multiple robots in a multi-block workspace. With the developments of intelligent robotics and ubiquitous technology, service robots are applicable for the wide area such as airports and train stations where multiple indoor GPS systems are required for the localization of the mobile robots. Indoor localization schemes using ultrasonic sensors have been widely studied due to its cheap price and high accuracy. However, ultrasonic sensors have some shortages of short transmission range and interferences with other ultrasonic signals. In order to use multiple robots in wide workspace concurrently, it is necessary to resolve the interference problem among the multiple robots in the localization process. This paper proposes an indoor localization system for concurrent multiple robots localization in a wide service area which is divided into multi-block for the reliable sensor operation. The beacon color code scheduling algorithm is developed to avoid the signal interferences and to achieve efficient localization with high accuracy and short sampling time. The performance of the proposed localization system is verified through the simulations and the real experiments.

• Aerospace Engineering and Technology
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• v.12 no.1
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• pp.128-136
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• 2013

Recently, the localization recognition system research has been studied using various sensors according to increased interest in autonomous navigation flight. In case of indoor environment which cannot support GPS information, we have to look for another way to recognize current position. The Image-based localization recognition system has been interested although there are lots of way to know current pose. In this paper, we explain the localization recognition system based on mark and implementation of autonomous navigation flight. In order to apply to real environment which cannot support marks, localization based on real-time 3D map building is discussed.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.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.

• International journal of advanced smart convergence
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• v.13 no.1
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• pp.37-47
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• 2024

This study presents the results of designing a system that determines the location of a person in an indoor environment based on a single IMU sensor attached to the tip of a person's shoe in an area where GPS signals are inaccessible. By adjusting for human footfall, it is possible to accurately determine human location and trajectory by correcting errors originating from the Inertial Measurement Unit (IMU) combined with advanced machine learning algorithms. Although there are various techniques to identify stepping, our study successfully recognized stepping with 98.7% accuracy using an artificial intelligence model known as Long Short-Term Memory (LSTM). Drawing upon the enhancements in our methodology, this article demonstrates a novel technique for generating a 200-meter trajectory, achieving a level of precision marked by a 2.1% error margin. Indoor pedestrian navigation systems, relying on inertial measurement units attached to the feet, have shown encouraging outcomes.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.1
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• pp.9-15
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• 2005

Most of location systems use RF signal. Because multipath is too severe at indoor environment, RF signal are usually used in outdoor positioning such as GPS. To overcome the difficulty at indoor positioning, m positioning is recently developed and is being vigorously studied. Some standardizations on UWB are in progress at IEEE 802.15 committee. In developing UWB positioning system, we should consider the synchronization of sensor network, positioning algorithm, sensor allocation, and so on. This paper presents a comparison of TDOA positioning algorithms that are widely used in location systems. Two algorithms are compared; one is derived by linearization, and the other is by analytic solution(CH algorithm). Simulation results show that the CH algorithm is superior to the linearized least square at indoor environment in that CH algorithm shows consistent positioning performance regardless of the visibility and geometry of basestations.