• Journal of Positioning, Navigation, and Timing
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• 제5권3호
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• pp.145-156
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• 2016

A variety of methods for indoor positioning systems have been underway to ensure the safety of emergency rescuers who are working in dangerous situations such as fire fighters. However, since most systems display locations of rescue workers in two-dimension (2D)-based maps, it is difficult for a commander located in the outside to recognize locations of rescuers inside the building intuitively. An augmented reality (AR)-based indoor positioning monitoring system can display locations of rescuer inside the building that can be seen by commanders to help intuitive recognition of positioning. To monitor AR-based indoor positioning, it is necessary to have an estimation technique of line of sight vector of observers. In the present study, an estimation technique of a line of sight vector using ultra-wide band tranceiver installed inside the indoor to trace locations is presented.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2016년도 추계학술발표대회
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• pp.168-171
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• 2016

In recent years, indoor localization in Wi-Fi environment has been researched for its location determining capability. The fingerprint and RF propagation models has been the main approach in determining indoor positioning. With the use of fingerprint, a low-cost, versatile localization system can be achieved without the use of external hardware. However, only a few research have been made on virtual access points (VAPs) among indoor localization models. In this paper, the idea of indoor localization system using fingerprint with the addition of VAP in Wi-Fi environment is discussed. The idea is to virtually add APs in the existing indoor Wi-Fi system, this would mean additional virtually APs in the network. The experiments of the proposed algorithm shows the positive results when 2VAPs are used compared with only APs. A combination of 3APs and 2VAPs had the lowest average error in all 4 scenarios with 3.99 meters.

• Journal of Positioning, Navigation, and Timing
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• 제10권1호
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• pp.49-54
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• 2021

Indoor positioning system becomes of increasing interests due to the demands for accurate indoor location information where Global Navigation Satellite System signal does not approach. Wi-Fi access points (APs) built in many construction in advance helps developing a Wi-Fi Received Signal Strength Indicator (RSSI) based indoor localization. This localization method first collects pairs of position and RSSI measurement set, which is called fingerprint database, and then estimates a user's position when given a query measurement set by comparing the fingerprint database. The challenge arises from nonlinearity and noise on Wi-Fi RSSI measurements and complexity of handling a large amount of the fingerprint data. In this paper, machine learning techniques have been applied to implement Wi-Fi based localization. However, most of existing indoor localizations focus on single position estimation. The main contribution of this paper is to develop multi-target localization by using deep neural, which is beneficial when a massive crowd requests positioning service. This paper evaluates the proposed multilocalization based on deep learning from a multi-story building, and analyses its learning effect as increasing number of target positions.

• 전기전자학회논문지
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• 제26권2호
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• pp.186-195
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• 2022

In this paper, we propose a new algorithm to improve the accuracy of indoor positioning techniques using Wi-Fi access points as beacon nodes. The proposed algorithm is based on the Weighted Centroid algorithm, a popular method widely used for indoor positioning, however, it improves some disadvantages of the Weighted Centroid method and also for other kinds of indoor positioning methods, by using the received signal strength correction method and genetic algorithm to prevent the signal strength fluctuation phenomenon, which is caused by the complex propagation environment. To validate the performance of the proposed algorithm, we conducted experiments in a complex indoor environment, and collect a list of Wi-Fi signal strength data from several access points around the standing user location. By utilizing this kind of algorithm, we can obtain a high accuracy positioning system, which can be used in any building environment with an available Wi-Fi access point setup as a beacon node.

• 설비공학논문집
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• 제21권3호
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• pp.193-200
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• 2009

The ventilation system of apartments can be divided by supply and exhaust fan, supply fan and exhaust free and supply free and exhaust fan. Recently, the individual ventilation system and central ventilation system which is combined cooling system with duct system are applied to apartment ventilation system. The airflow pattern is affected by location of supply unit and exhaust unit in indoor. This study is to investigate the proper distance between supply unit and exhaust unit using CFD. As a result of this study, the proper distance between supply unit and exhaust unit could be suggested at the interval of 3 m in supply and exhaust fan system and 2.5 m in supply fan and exhaust free.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권4호
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• pp.1090-1105
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• 2012

A multi-modal sensing M2M healthcare monitoring system for the continuous monitoring of patients under their natural physiological states or elderly persons with chronic diseases is summarized. The system is designed for homecare or the monitoring of the elderly who live in country side or small rest home without enough support from caregivers or doctors, instead of patient monitoring in big hospital environment. Further insights into the natural cause and progression of diseases are afforded by context-aware sensing, which includes the use of accelerometers to monitor patient activities, or by location-aware indoor tracking based on ultrasonic and RF sensing. Moreover, indoor location tracking provides information about the location of patients in their physical environment and helps the caregiver in the provision of appropriate support.

• 제어로봇시스템학회논문지
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• 제12권9호
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• pp.905-911
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• 2006

Smart homes are expected to offer various intelligent services by recognizing the residents' life pattern, health, and feeling. One of the key issues for realizing the smart home is how to detect the locations of residents. Currently, the research effort is focused on two approaches: terminal-based and non-terminal-based method. The terminal-based method employs a type of device that should be carried by the resident while the non-terminal-based method has no such device. This paper presents a novel non-terminal-based approach using an array of pyroelectric infrared sensors (PIRs) that can detect residents. The feasibility of the system is evaluated experimentally on a test bed.

• 제어로봇시스템학회논문지
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• 제12권9호
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• pp.868-875
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• 2006

The localization is one of the most important issues for mobile robot. This paper describes a novel localization system for the development of a location sensing network. The system comprises wirelessly controlled infrared landmarks and an image sensor which detects the pixel positions of infrared sources. The proposed localization system can operate irrespective of the illumination condition in the indoor environment. We describe the operating principles of the developed localization system and report the performance for mobile robot localization and navigation. The advantage of the developed system lies in its robustness and low cost to obtain location information as well as simplicity of deployment to build a robot location sensing network. Experimental results show that the developed system outperforms the state-of-the-art localization methods.

• 한국지능시스템학회논문지
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• 제18권4호
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• pp.537-542
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• 2008

Cricket is an excellent indoor location system and it can successfully solve many critical problems such as user privacy, decentralized administration. But in some practical applications, Cricket sometimes didn't provide location with enough accuracy, and was unable to determine when it was giving inaccurate information. For getting high-accuracy tracking performance from location data contaminated with noise, some types of filters are required. Kalman Filter is an efficient recursive filter that estimates the state of a dynamic system from a series of incomplete and noisy measurement. The filter is very powerful in the field of autonomous and assisted navigation. In this paper, we carry out comparative studies to validate the performance of the application of Kalman Filter to Cricket based localization system.

• 한국IT서비스학회지
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• 제9권3호
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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.