• KIISE Transactions on Computing Practices
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• v.23 no.4
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• pp.210-216
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• 2017

In the paper we propose and implement a new indoor localization system where the techniques of magnetic field based fingerprinting and pedestrian dead reckoning are combined. First, we determine a target's location by comparing acquired magnetic field values with a magnetic field map containing pre-collected field values at different locations and choosing the location having the closest value. As the target moves, we use pedestrian dead reckoning to estimate the expected moving path, reducing the maximum positioning error of the initial location. The system eliminates the problem of localization error accumulation in pedestrian dead reckoning with the help of the fingerprinting and does not require Wi-Fi AP infrastructure, enabling cost-effective localization solution.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.11
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• pp.1000-1008
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• 2014

Situation awareness for vehicles and pedestrians is very critical to ensure safety. While on-board sensors or systems can easily detect line-of-sight pedestrians, it is difficult to locate the positions of out-of-sight pedestrians especially with no GPS service. This paper proposes a method for accurate and on-time localization of indoor pedestrians by nearby vehicles. The proposed method is based on mobile ad-hoc networks among vehicles and pedestrians, without relying on infrastructures such as GPS, WiFi AP, and Bluetooth-based systems. Also, this paper develops a genetic algorithm to accurately and promptly locate pedestrians. Finally, simulation results are presented to quantitatively evaluate the proposed method compared to other studies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.3950-3969
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• 2021

Radio Frequency (RF)-based indoor localization technologies play significant roles in various Internet of Things (IoT) services (e.g., location-based service). Most such technologies require that all the devices comply with a specified technology (e.g., WiFi, ZigBee, and Bluetooth). However, this requirement limits its application scenarios in today's IoT context where multiple devices complied with different standards coexist in a shared environment. To bridge the gap, in this paper, we propose a cross-technology localization approach, which is able to localize target nodes using a different type of devices. Specifically, the proposed framework reuses the existing WiFi infrastructure without introducing additional cost to localize Non-WiFi device (i.e., ZigBee). The key idea is to leverage the interference between devices that share the same operating frequency (e.g., 2.4GHz). Such interference exhibits unique patterns that depend on the target device's location, thus it can be leveraged for cross-technology localization. The proposed framework uses Principal Components Analysis (PCA) to extract salient features of the received WiFi signals, and leverages Dynamic Time Warping (DTW), Gradient Boosting Regression Tree (GBRT) to improve the robustness of our system. We conduct experiments in real scenario and investigate the impact of different factors. Experimental results show that the average localization accuracy of our prototype can reach 1.54m, which demonstrates a promising direction of building cross-technology technologies to fulfill the needs of modern IoT context.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.12
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• pp.1240-1247
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• 2011

The localization of mobile robot in environment is a major concern in mobile robot navigation. So, many kinds of localization techniques have been researched for several years. Among them, the positioning system using ultrasound has received attention. Most of these ultrasonic positioning systems to synchronize the transmitters and receivers are used for RF (Radio Frequencies). However, due to the use of RF, the interference problems can not be avoided and the performance of radio frequencies directly affects the positioning performance. So we proposed the ultrasonic positioning system without synchronizing RF. The proposed system is based on existing USAT (Ultrasonic Satellite System) adopted infrastructure transmitting type, and consists of transmitter and receiver synchronizing modules instead of the radio frequency transmitters and receiver. The ultrasonic transmitters and receivers are synchronized individually by the transmitter and receiver synchronizing modules. In order to calculate the bias between the transmitter and receiver synchronizing modules, new positioning algorithm similar to GPS was proposed. The positioning performance of the improved USAT without synchronizing RF and the validity of the proposed positioning algorithm are verified and evaluated by experiments.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2019.05a
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• pp.159-160
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• 2019

It would be very important to localize people at risk as soon as possible in order to minimize the damage. Generally the infrastructure should be deployed additionally for indoor positioning system. In this paper, we proposed an indoor localization system for people at risk using the existing fire alarm networks. The system detects the signal of smart devices of people in danger immediately and let the main alarm controller ring all alarms in vessel and display the position. Thus, the proposed system can make the burden much less to deploy additional network and infrastructure.

• Knowledge Management Research
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• v.13 no.2
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• pp.19-35
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• 2012

This study empirically investigates the differences of dominant management problems (hereafter, DMPs) among transplants in different degree of localization, based on the exploratory case study on the nine transplants of Hyundai/Kia suppliers in US using AHP(Analytic Hierarchy Process) technique. On the results of the literature review, this study divides the DMPs of transplants into three main categories such as building human infrastructure, stabilizing manufacturing processes, and building learning network. Each categories is also divided into four subcategories. The degree of localization includes two variables such as the localization stage and the employee size of transplant. Main findings are as follows. First, 'Communication among Korean and local employees' is important DMP in all transplants examined. Second, 'Local adaptation of Korean manufacturing technology' and 'Education on the Korean culture and management practices' are more important DMPs for less-localized transplants than more-localized ones. On the contrary, 'Motivating local employees' is more important DMP for more-localized transplants than less-localized ones. Third, 'Education on the technology and quality' is more important DMP for transplants in post-production stage than in stabilization stage. On the contrary, 'Staffing local employees' is more important DMP for transplants in stabilization stage than in post-production stage. Fourth, 'Acquiring test and measurement equipments' is more important DMP for small-sized transplants than large-sized ones. On the contrary, 'adopting new technology' and 'Building local suppliers network' are more important DMPs for large-sized transplants than small-sized ones.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.2
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• pp.298-303
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• 2010

robots determine the location of the other robot using wireless sensors. Use it to decide how to move his. And go to any location, will make shape of column and line, circle. In this paper, we discuss problem in circle formation enclosing target which moves. It is method about enclosed invader in circle formation based on mutual localization of swarm robot without infrastructure. Therefore, use trilateration that do not need to know the value of the coordinates of reference points. So, Specify enclosed point for the number of robots base on between the relative position of the robot in the coordinate system. And particle filter is proposed to improve the accuracy of the location.

• Journal of the Korea Convergence Society
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• v.11 no.3
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• pp.37-43
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• 2020

Smartphone-based localization has been widely studied in many different scenarios. But as far as we know, few work has addressed the problem of localization in underground public transportation systems, where GPS signal and wireless infrastructure are not always available. Knowing the location of a train is necessary to develop a useful service for subway passengers. And so, estimation of motion state and stop station by using sensors on a smartphone is being studied for subway passengers. This paper proposes a localization method that uses a barometer and a magnetic sensor on a smartphone. The method proposed in this paper first estimates whether the train runs or stops according to the change in air pressure and the strength of the magnetic field. The altitude value and the magnetic field value are then used to estimate the exact stop station of the train. We evaluated the proposed method using data from the Seoul's subway line 5. Compared with previous methods, the proposed method achieves higher accuracy.

• Journal of Positioning, Navigation, and Timing
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• v.9 no.3
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• pp.151-156
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• 2020

A technology for calculating the position of a device is very important for users who receive positioning services, regardless of various indoor/outdoor or with/without any positioning infrastructure existence environments. One of the positioning resources widely used at present, LTE, is a typical infrastructure that can overcome the space limitation, however its positioning method based on the position of the LTE base station has low accuracy. A method of constructing a radio wave map of an LTE signal has been proposed as a method for overcoming the accuracy, but it takes a lot of time and cost to perform high-density collection in a wide area. In this paper, we describe a method of creating a high-density DB for the entire region by using vehicle-based partial collection data. To create a positioning database, we applied the idea of Generative Adversarial Network (GAN), which has recently been in the spotlight in the field of deep learning, and learned the collected data. Then, a virtually generated map which having the smallest error from the actual data is selected as the optimum DB. We verified the effectiveness of the positioning DB generation algorithm using the positioning data obtained from un-collected area.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.6
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• pp.336-342
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• 2017

Traffic can be localized by reducing the traffic load on the physical network by causing traffic to be generated at the end of the packet network. By localizing traffic, the IoT-based sensitive data-related security issues can be supported effectively. In addition, it can be applied effectively to the next-generation smart network environment without changing the existing network infrastructure. In this paper, a content priority scheme was applied to smart network-based IoT data. The IoT contents were localized to efficiently pinpoint the flow of traffic on the network to enable smart forwarding. In addition, research was conducted to determine the effective network traffic routes through content localization. Through this study, the network load was reduced. In addition, it is a network structure that can guarantee user quality. In addition, it proved that the IoT service can be accommodated effectively in a smart network-based environment.