• Korean Journal of Construction Engineering and Management
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• v.24 no.3
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• pp.42-51
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• 2023

Freeze and burst water meter in winter causes many social costs, such as meter replacement cost, inability of water use, and secondary damage by freezing water. The government is making efforts to modernize local waterworks, and in particular, is promoting SWM(Smart Water Management) project nationwide. In this study suggests a new freeze risk notification information service based on the temperature by IoT sensor inside the water meter box rather than outside temperature. In addition, in order to overcome the quantitative and regional limitation of IoT temperature sensors installed nationwide, and AI based temperature prediction model was developed that predicts the temperature inside water meter boxes based on data acquired from IoT temperature sensors and other information. Through the prediction model optimization process, a nationwide water meter freezing risk information service was convinced.

• Journal of Korean Society for Quality Management
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• v.52 no.1
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• pp.43-56
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• 2024

Purpose: The injection molding process, crucial for plastic shaping, encounters difficulties in sustaining product quality when replacing injection machines. Variations in machine types and outputs between different production lines or factories increase the risk of quality deterioration. In response, the study aims to develop a system that optimally adjusts conditions during the replacement of injection machines linked to molds. Methods: Utilizing a dataset of 12 injection process variables and 52 corresponding sensor variables, a predictive model is crafted using Decision Tree, Random Forest, and XGBoost. Model evaluation is conducted using an 80% training data and a 20% test data split. The dependent variable, classified into five characteristics based on temperature and pressure, guides the prediction model. Bayesian optimization, integrated into the selected model, determines optimal values for process variables during the replacement of injection machines. The iterative convergence of sensor prediction values to the optimum range is visually confirmed, aligning them with the target range. Experimental results validate the proposed approach. Results: Post-experiment analysis indicates the superiority of the XGBoost model across all five characteristics, achieving a combined high performance of 0.81 and a Mean Absolute Error (MAE) of 0.77. The study introduces a method for optimizing initial conditions in the injection process during machine replacement, utilizing Bayesian optimization. This streamlined approach reduces both time and costs, thereby enhancing process efficiency. Conclusion: This research contributes practical insights to the optimization literature, offering valuable guidance for industries seeking streamlined and cost-effective methods for machine replacement in injection molding.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.2
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• pp.178-185
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• 2011

In this paper, we propose the position estimation algorithm based on the multisensor fusion using equalization of state variables and feedback structure. First, the state variables measured from INS of main sensor with large error and DVL of assistance sensor with small error are measured before prediction phase. Next, the equalized state variables are entered to each filter and fused the enhanced state variables for prediction and update phases. Finally, the fused state variables are returned to the main sensor for improving the position estimation of UUV. For evaluation, we create the moving course of UUV by simulation and confirm the performance of position estimation by applying the proposed algorithm. The evaluation results show that the proposed algorithm is the best for position estimation and also possible for robust position estimation at the change period of moving courses.

• Journal of the Korea Institute of Military Science and Technology
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• v.26 no.1
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• pp.1-9
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• 2023

The skin structure of sensor pod mounted on the exterior of aircraft can be exposed to the acoustic dynamic load and static load such as aerodynamic pressure and inertial load during flight. Fatigue life prediction of structural model under acoustic load should be performed and also differential stiffness of model modified by static load should be considered. The acoustic noise test spectrum of MIL-STD-810G was applied to the structural model and the stress response power spectral density (PSD) was calculated. The frequency response analysis was performed with or without prestress induced by inplane static load, and the response spectrum was compared. Time series data was generated using the calculated PSD, and the time and frequency domain fatigue life were predicted and compared. The variation of stress response spectrum due to static load and predicted fatigue life according to the different structural model considering mean stress were examined and decreasing fatigue life was observed in the model with prestress of compressive static load.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.533-535
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• 2021

The differences between this study and previous studies are as follows. First, by building a cloud-based system using IoT technology, the system was built to monitor the status of buildings in real time from anywhere with an internet connection. Second, a model for predicting the future was developed using artificial intelligence (LSTM) and statistical (ARIMA) methods for the measured time series sensor data, and the effectiveness of the proposed prediction model was experimentally verified using a scaled-down building model. Third, a method to analyze the condition of a building more three-dimensionally by visualizing the structural deformation of a building by convergence of multiple sensor data was proposed, and the effectiveness of the proposed method was demonstrated through the case of an actual earthquake-damaged building.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.654-670
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• 2020

Workers at construction sites are easily exposed to many dangers and accidents involving falls, tripping, and missteps on stairs. However, researches on construction site monitoring system to prevent work-related injuries are still insufficient. The purpose of this study was to develop a wearable textile pressure insole sensor and examine its effectiveness in managing the real-time safety of construction workers. The sensor was designed based on the principles of parallel capacitance measurement using conductive textile and the monitoring system was developed by C# language. Three separate experiments were carried out for performance evaluation of the proposed sensor: (1) varying the distance between two capacitance plates to examine changes in capacitance charges, (2) repeatedly applying 1 N of pressure for 5,000 times to evaluate consistency, and (3) gradually increasing force by 1 N (from 1 N to 46 N) to test the linearity of the sensor value. Five subjects participated in our pilot test, which examined whether ascending and descending the stairs can be distinguished by our sensor and by weka assessment tool using k-NN algorithm. The 10-fold cross-validation method was used for analysis and the results of accuracy in identifying stair ascending and descending were 87.2% and 90.9%, respectively. By applying our sensor, the type of activity, weight-shifting patterns for balance control, and plantar pressure distribution for postural changes of the construction workers can be detected. The results of this study can be the basis for future sensor-based monitoring device development studies and fall prediction researches for construction workers.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.4
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• pp.469-475
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• 2015

This paper describes about the method for designing an extended Kalman filter to accurately measure the position of the spatial-phase system using a semiconductor sensor. Spatial position is expressed by the correlation of the rotated coordinate system attached to the body from the inertia coordinate system (a fixed coordinate system). To express the attitude, quaternion was adapted as a state variable, Then, the state changes were estimated from the input value which was measured in the gyro sensor. The observed data is the value obtained from the acceleration sensor. By matching between the measured value in the acceleration sensor and the predicted calculation value, the best variable was obtained. To increase the accuracy of estimation, designation of the extended Kalman filter was performed, which showed excellent ability to adjust the estimation period relative to the sensor property. As a result, when a three-axis gyro sensor and a three-axis acceleration sensor were adapted in the estimator, the RMS(Root Mean Square) estimation error in simulation was retained less than 1.7[$^{\circ}$], and the estimator displayed good property on the prediction of the state in 100 ms measurement period.

• Smart Structures and Systems
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• v.15 no.6
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• pp.1393-1410
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• 2015

An original sensor system based on Fiber Bragg Gratings (FBG) for the strain monitoring of an adaptive wing element is presented in this paper. One of the main aims of the SARISTU project is in fact to measure the shape of a deformable wing for performance optimization. In detail, an Adaptive Trailing Edge (ATE) is monitored chord- and span-wise in order to estimate the deviation between the actual and the desired shape and, then, to allow attaining a prediction of the real aerodynamic behavior with respect to the expected one. The integration of a sensor system is not trivial: it has to fit inside the available room and to comply with the primary issue of the FBG protection. Moreover, dealing with morphing structures, large deformations are expected and a certain modulation is necessary to keep the measured strain inside the permissible measure range. In what follows, the mathematical model of an original FBG-based structural sensor system is presented, designed to evaluate the chord-wise strain of an Adaptive Trailing Edge device. Numerical and experimental results are compared, using a proof-of-concept setup. Further investigations aimed at improving the sensor capabilities, were finally addressed. The elasticity of the sensor structure was exploited to enlarge both the measurement and the linearity range. An optimisation process was then implemented to find out an optimal thickness distribution of the sensor system in order to alleviate the strain level within the referred component.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.6
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• pp.9-13
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• 2019

In this paper, IoT based thermal sensor data and image sensor integrated environmental monitoring system for ship, and it is the monitoring system which can process and transmit the Full HD IP camera image and thermal data transmitted from the thermal module for processing and transmitting, and the viewer S/W is to be developed which provides in real time the information for actual surrounding temperature together with the image, and enables fire prediction which was impossible in the case of the existing equipment by estimating the temperature change as the thermal image is added to the image camera, and saves and analyzes all data while receiving the temperature data and image signal transmitted from the integrated thermal sensor environmental monitoring equipment for ship and displaying them as 2D on the monitoring system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.11B
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• pp.1200-1206
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• 2009

In this paper, we propose an energy-efficient MAC(Medium Access Control) protocol for processing context information in ubiquitous sensor network environments. CASMAC(Context Aware Sensor MAC) use context information for energy-efficient operation and its operation principle is as follows. First, we make scenarios with possible prediction for CASMAC. And then we save setted context information in server. When event occur at specific sensor node, and then it send three times sample data to server. According to context information, server process sample data. If server process sample data with event, it receive continuous data from event occur node by a transmission request signal. And then server send data transmission stop signal to event occur node when it do not need to data. If server process sample data with no event, it have not reply. Through we make energy consumption tables and an energy consumption model, we simulate analysis of CASMAC performance. In a result, we gains about 5.7 percents energy reduction compared to SMAC.