• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3858-3874
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• 2021

As an essential part of the urban transportation system, precise perception of the traffic flow parameters at the traffic signal intersection ensures traffic safety and fully improves the intersection's capacity. Traditional detection methods of road traffic flow parameter can be divided into the micro and the macro. The microscopic detection methods include geomagnetic induction coil technology, aerial detection technology based on the unmanned aerial vehicles (UAV) and camera video detection technology based on the fixed scene. The macroscopic detection methods include floating car data analysis technology. All the above methods have their advantages and disadvantages. Recently, indoor location methods based on wireless signals have attracted wide attention due to their applicability and low cost. This paper extends the wireless signal indoor location method to the outdoor intersection scene for traffic flow parameter estimation. In this paper, the detection scene is constructed at the intersection based on the received signal strength indication (RSSI) ranging technology extracted from the wireless signal. We extracted the RSSI data from the wireless signals sent to the road side unit (RSU) by the vehicle nodes, calibrated the RSSI ranging model, and finally obtained the traffic flow parameters of the intersection entrance road. We measured the average speed of traffic flow through multiple simulation experiments, the trajectory of traffic flow, and the spatiotemporal map at a single intersection inlet. Finally, we obtained the queue length of the inlet lane at the intersection. The simulation results of the experiment show that the RSSI ranging positioning method based on wireless signals can accurately estimate the traffic flow parameters at the intersection, which also provides a foundation for accurately estimating the traffic flow state in the future era of the Internet of Vehicles.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.4
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• pp.167-178
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• 2023

Our society is rapidly changing, and there is a growing demand for various convenience services in our daily lives. Among these services, railway and subway stations require tailored wayfinding services to accommodate individuals with disabilities. Currently, signage and information desks are the primary means of navigation. However, individuals with disabilities often rely on assistance from others due to physical discomfort or cognitive impairments. In this paper, we propose a customized wayfinding system within railway stations to assist individuals with disabilities. This system aims to ensure safe and convenient mobility in complex indoor environments, including transfer facilities.

• International Journal of Computer Science & Network Security
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• v.24 no.5
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• pp.135-155
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• 2024

Urban public health monitoring in smart cities focuses on the control of conditions and health challenges in urban environments. Considering the rapid spread of diseases and pandemics, it is important for health authorities to trace people carrying the virus. In smart cities, this tracing must be interoperable and intelligent, especially in indoor surfaces characterized by small distances between people. Therefore, to fight pandemics, it is necessary to start with the already-existing digital equipment of the Internet of Things, such as connected objects and smartphones. In this study, the developed system is employed to provide a social IoT network and suggest a strategy which allows reliable traceability without threatening the privacy of users. This IoT-based system allows respecting the social distance between persons sharing public services in smart cities without applying smartphone applications or severe confinement. It also permits a return to normal life in case of viral pandemic and ensures the much-desired balance between economy and health. The present study analyses previous proposed social distance systems then, unlike these studies, suggests an intelligent and distributed IoT based strategy for positioning students. Two scenarios of static and dynamic optimization-based placement of Bluetooth Low Energy devices are proposed and an experimental study shows the contribution and complementarity of the introduced contact tracing strategy with the applications on smartphones.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.1
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• pp.69-76
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• 2017

Bluetooth Low Energy (BLE), also known as Bluetooth Smart, has ultra-low power consumption; in fact, BLE-enabled devices can run on a single coin cell battery for several years. In addition, BLE can estimate the approximate distance between two devices using the Received Signal Strength Indication (RSSI) feature, enabling relatively precise navigation in indoor and small outdoor areas where GPS is not an option. In this paper, an experimental setup is presented in which BLE is used for navigation within a small outdoor area. BLE-based beacons are installed in fixed positions, which periodically transmit a universally unique identifier (UUID). A smart device receives the UUID and sends it to a database server using cellular or Wi-Fi technology. The server returns fixed position information corresponding to the received UUID codes, and the smart device uses that information to compute its current position based on relative signal strengths, and display it on a map. These results demonstrate the successful application of BLE technology for navigation in small outdoor areas. This system can be implemented for indoor navigation as well.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.5
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• pp.85-90
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• 2017

Indoor location-based services have been developed based on the Internet of Things technologies which measure and analyze users who are moving in their daily lives. These various indoor positioning technologies require separate hardware and have several disadvantages, such as a communication protocol which becomes complicated. Based on the fact that a reduction in signal strength occurs according to the distance due to the physical characteristics of the transmitted signal, RSSI technology that uses the received signal strength of the wireless signal used in this paper measures the strength of the transmitted signal and the intensity of the attenuated received signal and then calculates the distance between a transmitter and a receiver, which requires no separate costs and makes to implement simple measurements. It was applied calculating the value for the average RSSI and the RSSI filtering feedback. Filtering is used to reduce the error of the RSSI values that are measured at long distance.It was confirmed that the RSSI values through the average filtering and the RSSI values measured by setting the coefficient value of the feedback filtering to 0.5 were ranged from -61 dBm to - 52.5 dBm, which shows irregular and high values decrease slightly as much as about -2 dBm to -6 dBm as compared to general measurements.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.6
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• pp.281-285
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• 2010

We propose new identification method of LED location in indoor environment. It can transmit and receive position information and additional data, as applying OOK-SS watermarking method for LED transmission signal. Especially, we use a unipolar form code for watermarking spread code, because LED signal has unipolar characteristic. we analysis LED signal influence and interference with watermarking code, demonstrate usefulness of LED-ID using OOK-SS Watermarking.

• International Journal of Automotive Technology
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• v.8 no.6
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• pp.753-760
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• 2007

In this paper, a roll and pitch estimation algorithm using a set of accelerometers and wireless sensor networks(S/N) is presented for use in a passenger vehicle. While an inertial measurement unit(IMU) is generally used for roll/pitch estimation, performance may be degraded in the presence of longitudinal acceleration and yaw motion. To compensate for this performance degradation, a new roll and pitch estimation algorithm is proposed that uses an accelerometer array, global positioning system(GPS) and in-vehicle networks to get information from yaw rate and roll rate sensors. Angular acceleration and roll and pitch approximation are first calculated based on vehicle kinematics. A discrete Kalman filter is then applied to estimate both roll and pitch more precisely by reducing noise from the running engine and from road disturbance. Finally, the feasibility of the proposed algorithm is shown by comparing its performance experimentally with that of an IMU in the framework of an indoor test platform as well as a test vehicle.

• Journal of the Korean Society of Systems Engineering
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• v.16 no.1
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• pp.68-77
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• 2020

The shipbuilding and offshore industry is a large and complex assembly industry, which causes many safety accidents. The major accidents in the shipbuilding and offshore industry workplaces are stenosis, falling objects, dust, fire, explosions, and gas poisoning. The accident by worker in this industry mainly has three factors: frequent movement, narrow work space, and increased use of subcontractors. To control these factors, it is necessary to monitor the worker's location and work status. In this paper, a worker location monitoring system using inaudible sound wave was designd that can be used in environments with many metal barriers. The process included deriving stakeholder requirements, transforming to system requirements, designing system architecture, and developing prototype. The prototype was validated by third-party testing agency. As a result, it satisfied the designed performance and verified its feasibility.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.9
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• pp.2120-2126
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• 2010

This paper aims to realize the location tracking system using the Zigbee in the wireless sensor network. The wireless sensor network offers the user-oriented location tracking service in the ubiquitous environment. The location tracking service can track the location of an object or a person and provides it. The location tracking system realized in this paper can be used inside or outside without any black-out areas to measure the location of the moving nodes. In tracking inside the RSSI signals use and in tracking outside will connect with the GPS signals to track the location. Also, by using Zigbee, the wireless sensor network environment was established and by obtaining the location of the moving nodes, the real-time tracking is possible.

• Journal of Integrative Natural Science
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• v.4 no.3
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• pp.238-242
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• 2011

For any pattern matching based algorithm in WLAN environment, the characteristics of signal to noise ratio(SNR) to multiple access points(APs) are utilized to establish database in the training phase, and in the estimation phase, the actual two dimensional coordinates of mobile unit(MU) are estimated based on the comparison between the new recorded SNR and fingerprints stored in database. The system that uses the artificial neural network(ANN) falls in a local minima when it learns many nonlinear data, and its classification accuracy ratio becomes low. To make up for this risk, the SVM/ANN hybrid algorithm is proposed in this paper. The proposed algorithm is the method that ANN learns selectively after clustering the SNR data by SVM, then more improved performance estimation can be obtained than using ANN only and The proposed algorithm can make the higher classification accuracy by decreasing the nonlinearity of the massive data during the training procedure. Experimental results indicate that the proposed SVM/ANN hybrid algorithm generally outperforms ANN algorithm.