• Journal of Korea Society of Industrial Information Systems
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• v.27 no.1
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• pp.27-35
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• 2022

In the most IPS (Indoor Positioning System), it is available to specify the user's movement by sending a specific signal from a tag such as a beacon to multiple receivers. This method is very efficiently used in places where the number of people is limited. On the other hand, in large commercial facilities, it is nearly difficult to apply the existing IPS method because it is necessary to attach a tag to each customer. In this paper, we propose a system that uses an external sensor grid to identify people's movement without using tags. Each sensor node uses both an ultrasonic sensor and an infrared sensor to monitor people's movements and sends collected data to the main server through wireless transmission for easy system maintenance. The operation was verified using the FPGA board, and we designed a VLSI circuit in 180nm process.

• Journal of Internet of Things and Convergence
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• v.8 no.2
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• pp.1-6
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• 2022

This paper presents a regionalized time slotted channel hopping (TSCH) slotframe-based aerial data collection using wake-up radio. The proposed scheme aims to minimize the delay and energy consumption when an unmanned aerial vehicle (UAV) collects data from sensor devices in the large-scale service area. To this end, the proposed scheme divides the service area into multiple regions, and determines the TSCH slotframe length for each region according to the number of cells required by sensor devices in each region. Then, it allocates the cells dedicated for data transmission to the TSCH slotframe using the ID of each sensor device. For energy-efficient data collection, the sensor devices use a wake-up radio. Specifically, the sensor devices use a wake-up radio to activate a network interface only in the cells allocated for beacon reception and data transmission. The simulation results showed that the proposed scheme exhibited better performance in terms of delay and energy consumption compared to the existing scheme.

• Tunnel and Underground Space
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• v.32 no.2
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• pp.93-106
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• 2022

This study developed applications that allows truck drivers to record ore production data using smart devices at mine sites and to create a daily work report (operation report) in a PC environment. For this, four operating mines in Korea were selected as study areas, and daily work reports used there were investigated. The information elements included in the daily work report of each mine were analyzed. Because the information to be collected for writing ore production data and format of report are different for each mine, four types of applications were developed for the study areas. Ore production data could be recorded by receiving a signal from a Bluetooth beacon and by operating the application directly by the truck driver. The collected data files are uploaded to the cloud server, and the uploaded data files can be converted into a daily work report using the developed applications in a PC environment.

• Korean Journal of Heritage: History & Science
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• v.55 no.3
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• pp.178-188
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• 2022

This article cites examples of cultural heritages that urgently require protection measures, and the reinterpretation of beacons, fortresses, and extremities identified in the process of conducting a cultural heritage investigation of the DMZ and bordering areas. It is true that there are various difficulties involved in implementing thorough protection measures considering the reality of the two Koreas' division. Despite this, the "Ordinance for the Protection of Military Cultural Properties" and the "Act on the Protection and Investigation of Buried Cultural Heritage" have been enacted and are in effect. In particular, in the "Ordinance for the Protection of Military Cultural Properties," the value of protecting "military assets" is emphasized. The identification and investigation of cultural heritages in the DMZ and border areas must continue. Although field research is currently difficult, the primary investigation conducted by high-altitude terrain analysis and literature research is considered effective. Furthermore, there are parts that require correction and supplementation with future field investigations. Although some trial and error is expected during these various cultural heritage investigations, they need to continue.

• 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.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.5
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• pp.19-27
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• 2010

In this paper, we propose a scheme for real-time data retransmission in LR-WPAN to support the required QoS even in the severe channel error environments. In IEEE 802.15.4a, as the user data rate is supported up to 850Kbps, the real-time streaming data can be transferred more easily. In this research, we study the beacon-enabled mode in IEEE 802.15.4 LR-WPAN standard. In the proposed scheme, special slots are dynamical1y assigned for retransmission of the packet that fails during a real-time data service, and in the severe channel error environments a time diversity is acquired. Analytical results show that the proposed scheme is more robust and achieves a much higher throughput than the previous protocol in LR-WPAN.

• Journal of Korea Society of Industrial Information Systems
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• v.14 no.5
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• pp.33-41
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• 2009

In this paper, we propose a scheme for voice data retransmission in LR-WPAN to support the required QoS even in the severe channel error environments. In IEEE 802.15.4a, as the user data rate is supported up to 850Kbps, the voice streaming data can be transferred more easily. In this research, we study the beacon-enabled mode in IEEE 802.15.4 LR-WPAN standard with 250Kbps data rate. In the proposed scheme, special slots are dynamically assigned for retransmission of the packet that fails during a voice service, and in the severe channel error environments a time diversity is acquired. Analytical results show that the proposed scheme is more robust and achieves a much higher throughput than the previous protocol in LR-WPAN.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.17-25
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• 2023

The alarming global prevalence of Type 2 Diabetes Mellitus (T2DM) has catalyzed an urgent need for robust, early diagnostic methodologies. This study unveils a pioneering approach to predicting T2DM, employing the Extreme Gradient Boosting (XGBoost) algorithm, renowned for its predictive accuracy and computational efficiency. The investigation harnesses a meticulously curated dataset of 4303 samples, extracted from a comprehensive Chinese research study, scrupulously aligned with the World Health Organization's indicators and standards. The dataset encapsulates a multifaceted spectrum of clinical, demographic, and lifestyle attributes. Through an intricate process of hyperparameter optimization, the XGBoost model exhibited an unparalleled best score, elucidating a distinctive combination of parameters such as a learning rate of 0.1, max depth of 3, 150 estimators, and specific colsample strategies. The model's validation accuracy of 0.957, coupled with a sensitivity of 0.9898 and specificity of 0.8897, underlines its robustness in classifying T2DM. A detailed analysis of the confusion matrix further substantiated the model's diagnostic prowess, with an F1-score of 0.9308, illustrating its balanced performance in true positive and negative classifications. The precision and recall metrics provided nuanced insights into the model's ability to minimize false predictions, thereby enhancing its clinical applicability. The research findings not only underline the remarkable efficacy of XGBoost in T2DM prediction but also contribute to the burgeoning field of machine learning applications in personalized healthcare. By elucidating a novel paradigm that accentuates the synergistic integration of multifaceted clinical parameters, this study fosters a promising avenue for precise early detection, risk stratification, and patient-centric intervention in diabetes care. The research serves as a beacon, inspiring further exploration and innovation in leveraging advanced analytical techniques for transformative impacts on predictive diagnostics and chronic disease management.

• Journal of Internet of Things and Convergence
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• v.9 no.2
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• pp.71-76
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• 2023

In this paper, we propose a smoothed received signal strength indicator (RSSI)-based distance estimation using deep neural network (DNN) for accurate distance estimation in an environment where a single receiver is used. The proposed scheme performs a data preprocessing consisting of data splitting, missing value imputation, and smoothing steps to improve distance estimation accuracy, thereby deriving the smoothed RSSI values. The derived smoothed RSSI values are used as input data of the Multi-Input Single-Output (MISO) DNN model, and are finally returned as an estimated distance in the output layer through input layer and hidden layer. To verify the superiority of the proposed scheme, we compared the performance of the proposed scheme with that of the linear regression-based distance estimation scheme. As a result, the proposed scheme showed 29.09% higher distance estimation accuracy than the linear regression-based distance estimation scheme.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.5
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• pp.265-271
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• 2023

Recently, location information services are gradually expanding due to the development of information and communication technology. RSSI is widely used to extract indoor and outdoor locations. The indoor and outdoor location estimation methods using RSSI are less accurate due to the influence of radio wave paths, interference, and surrounding wireless devices. In order to improve this problem, a distance estimation method that takes into account the wireless propagation environment is necessary. Therefore, in this study, we propose a distance estimation algorithm that takes into account the radio wave environment. The proposed method estimates the distance by learning RSSI input and output considering the RBF neural network and the propagation environment. To evaluate the performance of the proposed method, the performance of estimating the location of the receiver within a range of up to 55[m] using a BLE beacon transmitter and receiver was compared with the average filter and Kalman filter. As a result, the distance estimation accuracy of the proposed method was 6.7 times higher than that of the average filter and Kalman filter. As shown in the results of this performance evaluation, if the method of this study is applied to location services, more accurate location estimation will be possible.