• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.1
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• pp.119-133
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• 2009

The purpose of this research is to accurately estimate the location of a device using the received signal strength indicator (RSSI) of IEEE 802.11 WLAN for location tracking in indoor environments. For the location estimation method, we adopted the calibration model. By applying the Adaptive Zone Based K-NNSS (AZ-NNSS) algorithm, which considers the velocity of devices, this paper presents a 9% improvement of accuracy compared to the existing K-NNSS-based research, with 37% of the K-NNSS computation load. The accuracy is further enhanced by using a Kalman filter; the improvement was about 24%. This research also shows the level of accuracy that can be achieved by replacing a subset of the calibration data with values computed by a numerical equation, and suggests a reasonable number of calibration points. In addition, we use both the mean error distance (MED) and hit ratio to evaluate the accuracy of location estimation, while avoiding a biased comparison.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.83-88
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• 2006

Many applications in the area of location-based services and personal navigation require nowadays the location determination of a user not only in outdoor environment but also indoor. To locate a person or object in a building, systems that use either infrared, ultrasonic or radio signals, and visible light for optical tracking have been developed. The use of WiFi for location determination has the advantage that no transmitters or receivers have to be installed in the building like in the case of infrared and ultrasonic based location systems. WiFi positioning technology adopts IEEE802.11x standard, by observing the radio signals from access points installed inside a building. These access points can be found nowadays in our daily environment, e.g. in many office buildings, public spaces and in urban areas. The principle of operation of location determination using WiFi signals is based on the measurement of the signal strengths to the surrounding available access points at a mobile terminal (e.g. PDA, notebook PC). An estimate of the location of the terminal is then obtained on the basis of these measurements and a signal propagation model inside the building. The signal propagation model can be obtained using simulations or with prior calibration measurements at known locations in an offline phase. The most common location determination approach is based on signal propagation patterns, namely WiFi fingerprinting. In this paper the underlying technology is briefly reviewed followed by an investigation of two WiFi positioning systems. Testing of the system is performed in two localization test beds, one at the Vienna University of Technology and the second at the Hong Kong Polytechnic University. First test showed that the trajectory of a moving user could be obtained with a standard deviation of about ${\pm}$ 3 m.

• Journal of the Korea Society for Simulation
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• v.32 no.3
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• pp.43-53
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• 2023

In this detailed and comprehensive study, our primary focus has been placed on accurately gauging the number of visitors and their real-time locations in commercial spaces. Particularly, in a real cafe, using security cameras, we have developed a system that can offer live updates on available seating and predict future congestion levels. By employing YOLO, a real-time object detection and tracking algorithm, the number of visitors and their respective locations in real-time are also monitored. This information is then used to update a cafe's indoor map, thereby enabling users to easily identify available seating. Moreover, we developed a model that predicts the congestion of a cafe in real time. The sophisticated model, designed to learn visitor count and movement patterns over diverse time intervals, is based on Long Short Term Memory (LSTM) to address the vanishing gradient problem and Sequence-to-Sequence (Seq2Seq) for processing data with temporal relationships. This innovative system has the potential to significantly improve cafe management efficiency and customer satisfaction by delivering reliable predictions of cafe congestion to all users. Our groundbreaking research not only demonstrates the effectiveness and utility of indoor location tracking technology implemented through security cameras but also proposes potential applications in other commercial spaces.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.465-468
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• 2007

An intelligent home network system using low-power and low-cost sensor nodes was designed and implemented. In Intelligent Home Network System, active home appliances control is composed of RSSI (Received Signal Strength Indicator) based user indoor location tracking, dynamic multi-hop routing, and learning integration remote-control. Through the remote-control learning, home appliances can be controlled in wireless network environment. User location information for intelligent service is calculated using RSSI based Triangle measurement method, and then the received location information is passed to Smoothing Algorithm to reduce error rate. In order to service Intelligent Home Network, moreover, the sensor node is designed to be held by user. The gathered user data is transmitted through dynamic multi-hop routing to server, and real-time user location & environment information are displayed on monitoring program.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.7
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• pp.898-903
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• 2020

In this paper, we propose an indoor logistic tracking system that identifies the location and inventory of the logistics in the room based on fingerprints. Through this, we constructed the actual infrastructure of the logistics center and designed and implemented the logistics management system. The proposed system collects the signal strength through the location terminal and generates the signal map to locate the goods. The location terminal is composed of a UHF RFID reader and a wireless LAN card, reads the peripheral RFID signal and the signal of the wireless AP, and transmits it to the web server. The web server processes the signal received from the location terminal and stores it in the database, and the user uses the data to produce the signal map. The proposed system combines UHF RFID with existing fingerprinting method to improve performance in the environment of querying multiple objects.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.1
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• pp.157-166
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• 2009

There is a growing interest in ubiquitous-related research and applications. Among them, GPS-based LBS have been developed and used actively. Recently, with the increase of large size buildings and disastrous events, indoor spaces are getting attention and related research activities are being carried out. Core technologies regarding indoor applications may include 3D indoor data modeling and localization sensor techniques that can integrate with indoor data. However, these technologies have not been standardized and established enough to be applied to indoor implementation. Thus, in this paper, we propose a method to build a relatively simple 3D indoor data modeling technique that can be applied to indoor location based applications. The proposed model takes the form of 2D-based multi-layered structure and has capability for 2D and 3D visualization. We tested three prototype applications using the proposed model; CA(cellular automata)-based 3D evacuation simulation, network-based routing, and indoor moving objects tracking using a stereo camera.

• IE interfaces
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• v.25 no.1
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• pp.114-126
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• 2012

This study describes a real-time location monitoring system developed for efficient operation of workplace in plant equipment maker. This monitoring system can be applied for indoor and outdoor working environment respectively. By using the real-time tracking system based on RTLS, it is possible to track worker's movement and location of working object under indoor working environment. For outdoor working environment, the real-time monitoring system based on IDGPS is applied for work safety and balanced workload. A case study is provided to evaluate the performance of the real-time monitoring system.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10d
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• pp.482-487
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• 2007

유비쿼터스 컴퓨팅 애플리케이션은 빈번히 위치 정보를 이용하기 때문에 모바일 노드들의 위치를 파악하여 서비스를 제공해 주는 것이 점차 중요하게 인식되고 있다. 여기서 모바일 노드들의 위치 추정은 센서 네트워크에서 노드들에게 좌표를 할당하는 것과 같은 의미이다. 센서 네트워크 환경에서 모바일 노드 위치 추정을 다루는 연구들이 늘어나고 있으나, 현재 제안된 거의 모든 연구들의 위치 추정 실험에서는 엔코더, 자이로, 가속도 센서 등을 이용해서 실제 이동량을 측정해야만 한다. 이 점에 착안하여, 본 연구에서는 어떤 추가적인 센서를 추가하지 않고 실험에서 얻은 모바일 노드의 좌표들을 카메라로 획득한 실제 영상에 맵핑시킴으로써 위치 추정 실험을 검증하기 위한 방법론을 제시하고, 제안한 방법론을 이용하여 크리켓 실내 위치 시스템(Cricket Indoor Location System)의 대표적인 두 가지 구조인 Active and Passive Infrastructure에서 무인 로봇의 위치 추정 실험 결과를 보여준다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.345-348
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• 2009

본 연구에서는 실내에서의 위치추적을 위해 가속도 센서와 각속도 센서를 이용한 위치추적기법을 제안하였다. 기존의 실내 위치추적기법은 전파의 세기를 이용하여 위치추적을 수행하는 RSSI기법과 초음파를 이용한 방법이 제시되었다. 하지만 기존 실내위치추적 기법에서는 좌표 값을 알고 있는 고정된 노드를 필수적으로 사용해야하는 단점이 있다. 본 연구에서는 이러한 단점을 보완하기위하여 착용형 노드에 가속도센서와 각속도 센서를 부착하고 이동속도와 방향을 계측하여 실내에서의 위치추적을 수행하고자 하였다. 이를 위해 3축 가속도 센서와 2축의 각속도 센서를 사용하였으며, 센서로부터 출력되는 아날로그신호를 계측 및 무선전송하기 위하여 Zigbee기반의 무선 센서노드를 사용하였다. 무선센서노드로부터 측정된 가속도신호와 각속도 신호의 분석을 통해 실내위치추적 가능성을 평가하였으며, 평가 결과 가속도센서와 각속도 센서를 이용한 실내위치추적의 가능성을 확인하였다.

• Journal of IKEEE
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• v.15 no.1
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• pp.76-85
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• 2011

In this paper, we analysed RSS characteristics by external factors and presented an efficient algorithm for real-time location tracking and its hardware system. The proposed algorithm enhanced the ranging accuracy using Kalman Filter based on the RSS DB. The location tracking system that consists of the tag, AP(Access Point), a data collector(Data Receiver) with IEEE 802.15.4(ZigBee) network environment, and location tracking application that reveal locations of each tag is implemented for the test environment. The location tracking system presented in this paper is implemented with MSP430 microprocessor manufactured by TI(Texas Instrument), CC2420 RF chipset and the location tracking application. With the results of the experiment, the proposed algorithm and the system can achieve the efficiency and the accuracy of location tracking with the average error of 19.12cm, and its standard deviation of 5.31cm in outdoor circumstance. Also, the experimental result shows that exact tracking of position in indoor circumstance cannot achieve because of vulnerable RSS with external circumstance.