• Journal of Aerospace System Engineering
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• 제18권4호
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• pp.27-33
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• 2024

This study deals with the demonstration of precision agriculture technology that can predict the health status of crops by analyzing the vegetation index (NDVI) using a drone equipped with a multi-spectral camera and an EO/IR camera. The multi-spectral camera measures crop reflectance to determine the vegetation index, while the EO/IR camera detects temperature changes in crops to evaluate water stress and health status. Data from this study can improve agricultural productivity and optimize the use of chemical fertilizers and pesticides. Moreover, integrating object recognition technology in the future could turn precision agriculture into a vital alternative for enhancing the sustainability of agriculture.

• Korean Journal of Remote Sensing
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• 제40권1호
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• pp.115-122
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• 2024

Multi-object tracking (MOT) is a vital component in understanding the surrounding environments. Previous research has demonstrated that MOT can successfully detect and track surrounding objects. Nonetheless, inaccurate classification of the tracking objects remains a challenge that needs to be solved. When an object approaching from a distance is recognized, not only detection and tracking but also classification to determine the level of risk must be performed. However, considering the erroneous classification results obtained from the detection as the track class can lead to performance degradation problems. In this paper, we discuss the limitations of classification in tracking under the classification uncertainty of the detector. To address this problem, a class update module is proposed, which leverages the class uncertainty estimation of the detector to mitigate the classification error of the tracker. We evaluated our approach on the VisDrone-MOT2021 dataset,which includes multi-class and uncertain far-distance object tracking. We show that our method has low certainty at a distant object, and quickly classifies the class as the object approaches and the level of certainty increases.In this manner, our method outperforms previous approaches across different detectors. In particular, the You Only Look Once (YOLO)v8 detector shows a notable enhancement of 4.33 multi-object tracking accuracy (MOTA) in comparison to the previous state-of-the-art method. This intuitive insight improves MOT to track approaching objects from a distance and quickly classify them.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• 제40권1호
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• pp.15-22
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• 2022

In order to improve the accuracy of the deep learning object detection technique, the effect of magnification rate conditions and seasonal factors on detection accuracy in aerial photographs and drone images was analyzed through experiments. Among the deep learning object detection techniques, Mask R-CNN, which shows fast learning speed and high accuracy, was used to detect the vehicle to be detected in pixel units. Through Seoul's aerial photo service, learning images were captured at different screen magnifications, and the accuracy was analyzed by learning each. According to the experimental results, the higher the magnification level, the higher the mAP average to 60%, 67%, and 75%. When the magnification rates of train and test data of the data set were alternately arranged, low magnification data was arranged as train data, and high magnification data was arranged as test data, showing a difference of more than 20% compared to the opposite case. And in the case of drone images with a seasonal difference with a time difference of 4 months, the results of learning the image data at the same period showed high accuracy with an average of 93%, confirming that seasonal differences also affect learning.

• Journal of the Institute of Convergence Signal Processing
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• 제24권4호
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• pp.236-241
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• 2023

Water quality problems in rivers, lakes, and estuaries have become serious in Korea. In order to overcome eutrophication of freshwater lakes and river basins, systematic management of water quality is necessary. To manage water quality in freshwater lakes and basins, apply hydrological models suitable for the basin and water quality models such as rivers and lakes to reduce water pollution based on the prediction results of these models. Improvement measures must be presented. In order to apply appropriate water pollution improvement measures in the watershed, accurate pollution sources must be identified and pollution loads must be predicted and presented. Based on GIS, the connection between the pollutant database and the hydrological and water quality prediction model will be integrated based on spatial location, making it possible to provide systematic support to improve watershed water quality by comprehensively including the water quality modeling process. In this paper, in order to accurately predict water pollution in freshwater lakes and river basins, a water quality model system is established using GIS-based spatial information to present a comprehensive water quality management method for freshwater lake basins in the future, and to systematically manage pollution sources through water quality modeling. This study was conducted to easily and efficiently operate hydrological and water quality models using automated spatial information.

• Journal of the Korea Society of Computer and Information
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• 제28권10호
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• pp.257-266
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• 2023

The aim of this study is to use media big data to understand the characteristics and changes in technology that prevents wandering and missing for dementia patients as well as supports safe walking since 1990 until recently. BigKinds as a media big data was used to conduct an analysis in two stages. In the results, first, the media reports began to be reported in the early 2000s, and it increased after 2014. Second, regarding to the characteristics of changes in technology and device utilization, there has been a change to advanced technology that combines AI and IoT, focusing on GPS. Drone has recently increased in media report, however problems of personal information security need to be resolved. Third, technology development focused on location identification by police and guardians. Based on the results, technology development and community cooperation for dementia patient were discussed.

• Journal of Convergence for Information Technology
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• 제10권12호
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• pp.236-244
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• 2020

In this research a suspended solid transport experiment was conducted in the river experiment center to find the characteristics and dispersion of the material. Modeling by the particle dispersion model was also executed to reproduce the suspended solid transport. The suspended solid was consisted of a mixture of silica and water using a mixing equipment, which was then introduced into a real-scale flume and measured with the laser-diffraction based particle size analyzer(LISST) to find the concentration of the material. The comparison between the measured suspended solid concentration using drone images and particle size analyzers, with the model showed a good match overall, which proved the applicability of the model. Along with finding the model applicability, the research showed the potential for suspended solid estimation in high flow situations with high rainfall.

• Journal of Navigation and Port Research
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• 제44권6호
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• pp.557-563
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• 2020

Digital Twin Technology is currently being utilized in many industries and logistics seems soon to follow that trend. Currently, technology introduction to container terminals is restrictedly developing. In reviewing the existing literature, it became clear that research on the application of Digital Twin technology for container terminals is deficient. This study fulfilled AHP and IPA analysis causing fields to adjust priority at the container terminal. The result of analysis on the urgent necessity of adjustable fields' detailed elements from Digital Twin Technology, ATC, intelligent CCTV, and container yards, and showed that they were of the highest priority level. Also, VR/AR Equipment, AYT, Smart Container, Automated Container Delivery Facility, Refrigerated/Freezer Container, Wearable Device for Port Maintenance, and Smart Buoy were reviewed in detail. Our group suggests AQC, Berth, AGV, ASC, Apron, and Automated Mooring as potentially useful Digital Twin Technologies. Finally, our research suggests the OSS equipment, intermodal linkage facility, intelligent drone, and hazardous material storage are areas of low priority.

• The Journal of Sustainable Design and Educational Environment Research
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• 제19권4호
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• pp.78-87
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• 2020

This study proposed the basic data that contributes to inducing an effective construction plan through the application of the 4th industrial technology to construct a school building that can guarantee the five goals of construction management: cost, process, quality, safety, and environmental management. To this end, 3D printing, drones, robot automation, and augmented reality technologies that are highly usable in construction sites were identified for construction workers. As part of this, related literature and research data were investigated. The selected 4th industrial technology was investigated and analyzed on how it was used for cost, process, quality, safety, and environmental management in a detailed school construction process. As a result of the analysis, significant results were found for the application plan of the 4th industrial technology in school construction for cost, process, quality, safety, and environmental management.

• Journal of the Korea Institute of Military Science and Technology
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• 제27권1호
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• pp.1-7
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• 2024

Weather is one of the main causes of aircraft accidents, and among the phenomena caused by weather, icing is a phenomenon in which an ice layer is formed when an object exposed to an atmosphere below a freezing temperature collides with supercooled water droplets. If this phenomenon occurs in the rotor blades, it causes defects such as severe vibration in the airframe and eventually leads to loss of control and an accident. Therefore, it is necessary to foresee the icing situation so that it can ascend and descend at an altitude without a freezing point. In this study, vibration data in normal and faulty conditions was acquired, data features were extracted, and vibration was predicted through deep learning-based algorithms such as CNN, LSTM, CNN-LSTM, Transformer, and TCN, and performance was compared to evaluate blade icing. A method for minimizing operating loss is suggested.

• The Journal of the Convergence on Culture Technology
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• 제10권4호
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• pp.701-710
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• 2024

This study conducted a survey of companies in the aviation, drone, and Urban Air Mobility (UAM) sectors to analyze the educational and workforce needs, identifying essential competencies and technical training required. The study also proposed potential areas for collaboration between universities and industry regarding educational methods. Key findings and implications of the survey were derived. The results indicated that the most critical consideration for hiring was job-specific skills in the respective field. The most essential quality for workforce training was identified as enhancing the ability to use various equipment and software related to the major field. In the UAM sector, there was a high demand for personnel and education related to aircraft and components, with the highest demand being for lightweight manufacturing technology for aircraft. This study can serve as foundational data for addressing the educational needs in this field.