• Journal of Korean Tunnelling and Underground Space Association
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• v.25 no.6
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• pp.509-523
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• 2023

The high-level nuclear waste (HLW) repository is exposed to complex environmental conditions consisting of high temperature, high humidity, and radiation, resulting in structural deterioration. Therefore, structural health monitoring is essential, and piezo sensors are used to detect cracks and estimate strength. However, since the monitoring sensors installed in the disposal tunnel and disposal container cannot be replaced or removed, the quantitative life of the monitoring sensor and its suitability must be assessed. In this study, the life of a piezo sensor for monitoring was assessed using an accelerated life test (ALT). The failure mode and mechanism of the piezo sensor under high temperature conditions were determined, and temperature stress's influence on the piezo sensor's life was analyzed. ALT was conducted on temperature stress and the relationship between temperature stress and piezo sensor life was suggested. The life of the piezo sensor was assessed using the Weibull probability distribution and the Arrhenius acceleration model. The suggested relationship can be used in multiple stress ALT designs for more precise life assessment.

• Journal of Broadcast Engineering
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• v.22 no.6
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• pp.713-723
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• 2017

Since the panoramic image can overcome the limitation of the viewing angle of the camera and have a wide field of view, it has been studied effectively in the fields of computer vision and stereo camera. In order to generate a panoramic image, stitching images taken by a plurality of general cameras instead of using a wide-angle camera, which is distorted, is widely used because it can reduce image distortion. The image stitching technique creates descriptors of feature points extracted from multiple images, compares the similarities of feature points, and links them together into one image. Each feature point has several hundreds of dimensions of information, and data processing time increases as more images are stitched. In particular, when a panorama is generated on the basis of an image photographed by a plurality of unspecified cameras with respect to an object, the extraction processing time of the overlapping feature points for similar images becomes longer. In this paper, we propose a preprocessing process to efficiently process stitching based on an image obtained from a number of unspecified cameras for one object or environment. In this way, the data processing time can be reduced by pre-grouping images based on camera sensor information and reducing the number of images to be stitched at one time. Later, stitching is done hierarchically to create one large panorama. Through the grouping preprocessing proposed in this paper, we confirmed that the stitching time for a large number of images is greatly reduced by experimental results.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.3
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• pp.99-110
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• 2015

Internet-of-Things(IoT) is the computing paradigm converged with different technologies, where diverse devices are connected via the wireless network, acquire environmental information from their equipped sensors, and actuated. IoT applications typically provide smart services to users by interacting with multiple devices connected to the network and are designed by integrating multiple technologies such as sensor network, communication technologies, and software engineering. Moreover, since the concept of IoT has been introduced recently, most of the researches are in the beginning step, which is too early to be practically applied. Due to these facts, developing IoT application results in unconventional technical challenges which have not been observed in typical software applications. And, it is not straightforward to apply conventional project guidelines to IoT application development projects. Hence, there can be many difficulties to successfully complete the projects. Therefore, for successful completion of the projects, we analyze technical challenges occurring in all phases of the project lifecycle, i.e. project preparation stage and development stage. And, we propose the effective solutions to overcome the issues. To verify identified issues and presented solutions, we present the result of applying the solutions to an IoT application development. Through the case study, we evaluate how reasonable the unconventional technical issues are generated and analyze effectiveness of applying the solutions to the application.

• Journal of Biosystems Engineering
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• v.36 no.5
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• pp.326-333
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• 2011

The need for rapid on-site monitoring of hydroponic macronutrients has led to the use of ion-selective electrodes, because of their advantages over spectrophotometric methods, including simple methodology, direct measurement of analyte, sensitivity over a wide concentration range, and low cost. Stability and repeatability of response can be a concern when using multiple ion-selective electrodes to measure concentrations in a series of samples because accuracy might be limited by drifts in electrode potential. A computer-based measurement system could improve accuracy and precision because of both consistent control of sample preparation and easy calibration of sensors. Our goal was to investigate the applicability of a cobalt-based electrode used in conjunction with a laboratory-made automated test stand for quantitative determination of ${PO_4}^-$ in hydroponic solution. Six hydroponic solutions were prepared by diluting highly concentrated paprika hydroponicsolution to provide a concentration range of 1 to 300 ppm $PO_4$-P. A calibration curve relating electrode response to phosphate in paprika hydroponic solution titrated to pH 4 with 0.025M KHP was developed based on the Nikolskii-Eisenman equation with a coefficient of determination ($R^2$) of 0.94. The laboratory-made test stand consisting of three cobalt-based electrodes measured phosphate concentrations similar to those obtained with standard laboratory methods (a regression slope of 0.98 with $R^2$ = 0.80). However, the y intercept was relatively high, 30 ppm, probably due to the relatively large amount of variation present among multiple measurements of the same sample. Further studies on the high variation in EMFs obtained with cobalt electrodes during replicate measurements were required for P estimations comparable to those obtained with standard laboratory instruments.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.2 no.2 s.3
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• pp.43-54
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• 2003

As the demand for ubiquitous mobile wireless Internet grows, vehicles are receiving a lot of attention as new networking platforms. The demand for 4G all-IP networks encourages vehicle networks to be connected using IPv6. By means of network mobility (NEMO) support, we can connect sensors, controllers, local ,servers as well as passengers' devices of a vehicle to the Internet through a mobile router. The mobile router provides the connectivity to the Internet and mobility transparency for the rest of the mobile nodes of an in-vehicle nv6 network. So, it is .important for the mobile router to assure reliable connection and a sufficient data rate for the group of nodes behind it. To provide reliability, this paper proposes an adaptive multihoming architecture of multiple mobile routers. Proposed architecture makes use of different mobility characteristics of different vehicles. Simulation results with different configurations show that the proposed architecture increases session preservation thus increases reliability and reduces packet loss. We also show that the proposed architecture is adaptive to heterogeneous access environment which provide different access coverage areas and data rates. The result shows that our architecture achieves sufficient data rates as well as session preservation.

• Smart Media Journal
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• v.10 no.3
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• pp.31-38
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• 2021

It is hard to predict when and where a fall accident will happen. Also, if rapid follow-up measures on it are not performed, a fall accident leads to a threat of life, so studies that can automatically detect a fall accident have become necessary. Among automatic fall-accident detection techniques, a fall detection scheme using an IMU (inertial measurement unit) sensor attached to a wrist is difficult to detect a fall accident due to its movement, but it is recognized as a technique that is easy to wear and has excellent accessibility. To overcome the difficulty in obtaining fall data, this study proposes an algorithm that efficiently learns less data through machine learning such as KNN (k-nearest neighbors) and SVM (support vector machine). In addition, to improve the performance of these mathematical classifiers, this study utilized feature data aquired in the frequency space. The proposed algorithm analyzed the effect by diversifying the parameters of the model and the parameters of the frequency feature extractor through experiments using standard datasets. The proposed algorithm could adequately cope with a realistic problem that fall data are difficult to obtain. Because it is lighter than other classifiers, this algorithm was also easy to implement in small embedded systems where SIMD (single instruction multiple data) processing devices were difficult to mount.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.173-184
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• 2018

As the portable traffic information collection system using probe vehicles spreads, it is becoming possible to collect road hazard information such as portholes, falling objects, and road surface freezing using in-vehicle sensors in addition to existing traffic information. In this study, we developed a integration and decision algorithm that integrates time and space in real time when multiple probe vehicles detect events such as road hazard information based on GPS coordinates. The core function of the algorithm is to determine whether the road hazard information generated at a specific point is the same point from the result of detecting multiple GPS probes with different GPS coordinates, Generating the data, (3) continuously determining whether the generated event data is valid, and (4) ending the event when the road hazard situation ends. For this purpose, the road risk information collected by the probe vehicle was processed in real time to achieve the conditional probability, and the validity of the event was verified by continuously updating the road risk information collected by the probe vehicle. It is considered that the developed hybrid processing algorithm can be applied to probe-based traffic information collection and event information processing such as C-ITS and autonomous driving car in the future.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.10
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• pp.345-352
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• 2022

Recent LiDAR(Light Detection And Ranging) sensor is used for scanning object around in real-time. This sensor can detect movement of the object and how it has changed. As the production cost of the sensors has been decreased, LiDAR begins to be used for various industries such as facility guard, smart city and self-driving car. However, LiDAR has a large input data size due to its real-time scanning process. So another way for processing a large amount of data are needed in LiDAR system because it can cause a bottleneck. This paper proposes edge computing to compress massive point cloud for processing quickly. Since laser's reflection range of LiDAR sensor is limited, multiple LiDAR should be used to scan a large area. In this reason multiple LiDAR sensor's data should be processed at once to detect or recognize object in real-time. Edge computer compress point cloud efficiently to accelerate data processing and decompress every data in the main cloud in real-time. In this way user can control LiDAR sensor in the main system without any bottleneck. The system we suggest solves the bottleneck which was problem on the cloud based method by applying edge computing service.

• Journal of Service Research and Studies
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• v.11 no.2
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• pp.118-130
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• 2021

This study designs and validates a greenhouse complex environmental control algorithm with a multi-phase processing scheme that can combine and control actuators according to the degree of change in the greenhouse environment. The composite environmental control system is a system in which the complex environmental controller analyzes the information detected by sensors and operates appropriately actuators to maintain the crop growth environment. A composite environmental controller directs control devices driving actuators through a composite environmental control algorithm, which calculates the values necessary for the operation of the control devices. Most existing algorithms carry out control procedures on a single phase by iteration cycle, which can cause abnormal changes in the greenhouse environment due to errors in output. The proposed algorithm distributes control procedures over multiple phases: environmental control, environmental control, and device operation, and every iteration cycle, detects environmental changes in the environmental control phase first, and then combines control devices that can control the environment in the environmental control phase, and finally, performs the controls to derive the actuators in the device operation phase. The proposed algorithm is designed based on the analysis of the relationship between greenhouse environmental elements and control devices deriving actuators. According to verification analysis, the multi-phase processing scheme provides room to modify or supplement the setting value and enables the control devices to reflect changes in the associated environmental components.

• Journal of the Korea Computer Graphics Society
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• v.30 no.3
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• pp.171-178
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• 2024

Exercises using a Balance Board (BB) are effective in developing balance, strengthening core muscles, and improving physical fitness and concentration. In particular, the Smart Balance Board (SBB), which integrates with various digital content, provides appropriate feedback compared to traditional balance boards, maximizing the effectiveness of the exercise. However, most systems only offer visual and auditory feedback, failing to evaluate the impact on user engagement, interest, and the accuracy of exercise postures. This study proposes an Immersive Smart Balance Board (I-SBB) that utilizes multiple sensors to enable training with various feedback mechanisms and precise postures. The proposed system, based on Arduino, consists of a gyro sensor for measuring the board's posture, a communication module for wired/wireless communication, an infrared sensor to guide the user's foot placement, and a vibration motor for tactile feedback. The board's posture measurements are smoothly corrected using a Kalman Filter, and the multi-sensor data is processed in real-time using FreeRTOS. The proposed I-SBB is shown to be effective in enhancing user concentration and engagement, as well as generating interest, by integrating with diverse content.