• Journal of the Korean Society of Industry Convergence
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• v.26 no.6_2
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• pp.1063-1071
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• 2023

Unmanned aerial vehicles (UAVs, drones) are becoming increasingly useful in a variety of fields. Advances in UAV and camera technology have made it possible to equip them with ultra-high resolution sensors and capture images at low altitudes, which has improved the reliability and classification accuracy of object identification on the ground. The distinctive contribution of this study is the derivation of sensor-specific performance metrics (GRD/GSD), which shows that as the GSD increases with altitude, the GRD value also increases. In this study, we identified the characteristics of various onboard sensors and analysed the image quality (discrimination resolution) of aerial photography results using UAVs, and calculated the shooting conditions to obtain the discrimination resolution required for reading ground objects.

• Proceeding of EDISON Challenge
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• 2017.03a
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• pp.290-303
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• 2017

This paper aims to build a drone platform based on an optimum design of its single arm. We assumed its single arm as a cantilevered beam with a tip mass. Based on the numerical optimization theory, we conducted validation and optimization of a new design by comparing the results with the similar ones obtained by ANSYS. Finally, this design is reflected in the control simulation, and the requirement of an optimum structural design considering the resonance situation is demonstrated.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.4
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• pp.225-232
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• 2022

Recently, unmanned logistics delivery systems, such as UAV (Unmanned Aerial Vehicle, written as drone below) and autonomous robot delivery systems, have been implemented in many countries due to the rapid development of autonomous driving technology. The development of these new types of advanced unmanned logistics delivery systems is essential not only to become a leading logistics company but also to secure national competitiveness. In this paper, the application of the unmanned logistics delivery system was investigated in terms of market trends, overall technology level of last mile delivery drone and autonomous delivery robot. The direction of response to changes in the last mile delivery service market was checked through a comparison of the technological level between domestic companies that produce last mile devices and advanced foreign companies. As a result of this technology level analysis, the difference between domestic companies and advanced companies was shown using tables and figures to show their relative levels. The results of this analysis reflect the opinions of experts in the field of last-mile delivery technology. In addition, the technology level of unmanned logistics delivery systems for each country was analyzed based on the number of related technology patents. Lastly, insights for the technology level analysis of unmanned last mile delivery systems were proposed as a conclusion.

• Journal of Distribution Science
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• v.14 no.5
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• pp.51-57
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• 2016

Purpose - In the year of 2015 and 2016, one of the items that got attention in CES was a drone. It has been 100 years since a drone emerged, but most were used for military purposes. As its use became diverse as of 2010, it got attention of the general public. In Korea, it was in 2011 that a drone was known to the public through an aerial video shooting for television program. This study tried to come up with suggestions by comparing domestic with overseas cases, and tried to consider the related technologies and systems with applying the role of drones in logistics service. Research design, data, and methodology - The overseas cases were regarded as drone's logistical purpose. The Prime Air service by US Amazon is still not commercialized and under pre-testing due to Federal Aviation Regulations, although it started in 2013. In Germany, DHL succeeded in delivering service testing which is called Parcelcopter, but it is not commercialized yet. Other than these, there are more attempts to prepare logistics service in China with Taobao, in France with Geopost's test, and in Africa. In Korea, CJ Korea Express tested delivery with a self-developed drone Results - In order to study for utilizing drones for logistics as the prerequisites, some overseas and domestic cases, which are currently considered, were reviewed. Also, the technologies and institutional requirements to commercialize drones for logistical purpose were reviewed. The reasons for using drones in logistics is to ensure the price competitiveness by reducing cost. The empirical test also will be needed because drone pilot areas are designated by ministry of land, infrastructure and transport. Conclusions - In order to utilize drones in logistics and foster the industry, this study would like to suggest the followings. First of all, size of drones for logistics needs to be fixed and their operating system should be standardized. Centralized investment resources are needed through standardization to ensure the market occupancy. Secondly, it is necessary to get the converged businesses that do research, develop and commercialize drones with the investment of private sector. Example can be found in Korea aerospace Industries. We can respond to the rapid growth of the market with intensive investing by integrating the private sector investment. Thirdly, institutional arrangements are needed to be established quickly. In the case of high-technologies like drones, institutional support often does not follow the rapid development of the technology. The problems can be found in securing drones-only airspace, creating drone-specialized pilot's license, matters related to remote controller and complementary regulations for drones in Aviation Act. If these regulations are not prepared or complemented at the right timing, technologies cannot be commercialized even though the development is completed. Fourthly, there is a need to secure the transparency regarding possible privacy and personal information protection problem while operating drones. Finally, in order to foster this new industry, government should focus on supporting R&D more in the long term than short term outcomes.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.1
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• pp.768-773
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• 2020

In large-scale land development for the rational use and management of national land resources, the use of geospatial information is essential for the efficient management of projects. Recently, drone LiDAR (Light Detection And Ranging) has attracted attention as an effective geospatial information construction technique for large-scale development areas, such as housing site construction and open-pit mines. Drone LiDAR can be classified into a method using SLAM (Simultaneous Localization And Mapping) technology and a GNSS (Global Navigation Satellite System)/IMU (Inertial Measurement Unit) method. On the other hand, there is a lack of analytical research on the application of drone LiDAR or the characteristics of each method. Therefore, in this study, data acquisition, processing, and analysis using SLAM and GNSS/IMU type drone LiDAR were performed, and the characteristics and utilization of each were evaluated. As a result, the height direction accuracy of drone LiDAR was -0.052~0.044m, which satisfies the allowable accuracy of geospatial information for mapping. In addition, the characteristics of each method were presented through a comparison of data acquisition and processing. Geospatial information constructed through drone LiDAR can be used in several ways, such as measuring the distance, area, and inclination. Based on such information, it is possible to evaluate the safety of large-scale development areas, and this method is expected to be utilized in the future.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.119-125
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• 2023

Through the Ukraine-Russia war, the military importance of drones is being reassessed, and North Korea has completed actual verification through a drone provocation towards South Korea at 2022. Furthermore, North Korea is actively integrating artificial intelligence (AI) technology into drones, highlighting the increasing threat posed by drones. In response, the Republic of Korea military has established Drone Operations Command(DOC) and implemented various drone defense systems. However, there is a concern that the efforts to enhance capabilities are disproportionately focused on striking systems, making it challenging to effectively counter swarm drone attacks. Particularly, Air Force bases located adjacent to urban areas face significant limitations in the use of traditional air defense weapons due to concerns about civilian casualties. Therefore, this study proposes a new passive air defense method that aims at disrupting the object detection capabilities of AI models to enhance the survivability of friendly aircraft against the threat posed by AI based swarm drones. Using laser-based adversarial examples, the study seeks to degrade the recognition accuracy of object recognition AI installed on enemy drones. Experimental results using synthetic images and precision-reduced models confirmed that the proposed method decreased the recognition accuracy of object recognition AI, which was initially approximately 95%, to around 0-15% after the application of the proposed method, thereby validating the effectiveness of the proposed method.

• Journal of Korean Society of Rural Planning
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• v.30 no.1
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• pp.57-66
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• 2024

This study aimed to develop a precise vegetation cover classification model for small streams using the combination of drone remote sensing and support vector machine (SVM) techniques. The chosen study area was the Idong stream, nestled within Geosan-gun, Chunbuk, South Korea. The initial stage involved image acquisition through a fixed-wing drone named ebee. This drone carried two sensors: the S.O.D.A visible camera for capturing detailed visuals and the Sequoia+ multispectral sensor for gathering rich spectral data. The survey meticulously captured the stream's features on August 18, 2023. Leveraging the multispectral images, a range of vegetation indices were calculated. These included the widely used normalized difference vegetation index (NDVI), the soil-adjusted vegetation index (SAVI) that factors in soil background, and the normalized difference water index (NDWI) for identifying water bodies. The third stage saw the development of an SVM model based on the calculated vegetation indices. The RBF kernel was chosen as the SVM algorithm, and optimal values for the cost (C) and gamma hyperparameters were determined. The results are as follows: (a) High-Resolution Imaging: The drone-based image acquisition delivered results, providing high-resolution images (1 cm/pixel) of the Idong stream. These detailed visuals effectively captured the stream's morphology, including its width, variations in the streambed, and the intricate vegetation cover patterns adorning the stream banks and bed. (b) Vegetation Insights through Indices: The calculated vegetation indices revealed distinct spatial patterns in vegetation cover and moisture content. NDVI emerged as the strongest indicator of vegetation cover, while SAVI and NDWI provided insights into moisture variations. (c) Accurate Classification with SVM: The SVM model, fueled by the combination of NDVI, SAVI, and NDWI, achieved an outstanding accuracy of 0.903, which was calculated based on the confusion matrix. This performance translated to precise classification of vegetation, soil, and water within the stream area. The study's findings demonstrate the effectiveness of drone remote sensing and SVM techniques in developing accurate vegetation cover classification models for small streams. These models hold immense potential for various applications, including stream monitoring, informed management practices, and effective stream restoration efforts. By incorporating images and additional details about the specific drone and sensors technology, we can gain a deeper understanding of small streams and develop effective strategies for stream protection and management.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.125-132
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• 2024

The purpose of this study is to discover a drone utilization model tailored to local characteristics, propose directions for building a drone demonstration city based on demand surveys for drone activation, and suggest ways to utilize and support a drone application system. First, according to the survey results, there was a high understanding of and necessity for drone demonstration projects, particularly in addressing urban issues, which were deemed to have a significant impact. Second, based on the analysis of priorities and short- and long-term approaches, disaster-related tasks were evaluated as a priority, requiring an approach through medium- to long-term strategies. Third, it was noted that budgetary considerations emerged as the most critical issue during project implementation. Practitioners and experts expressed willingness to actively introduce drone-based technologies into their work when budget and technology were ready. Budgetary constraints were identified as the most significant obstacle to proper implementation, emphasizing the need for resolution. Fourth, the necessity of demand surveys during project development was identified in certain areas. Demand surveys were deemed essential for drone-based demonstration city construction, and a survey indicated that public leadership in this regard was also necessary. Fifth, concerning approaches in specific areas, the field of safety and disaster management was highlighted as the most crucial for application.

• Electronics and Telecommunications Trends
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• v.38 no.3
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• pp.11-19
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• 2023

Drones, which were early operated by remote control, have evolved to enable autonomous flight by combining various sensors and software tools. In particular, autonomous flight of drones was possible since the application of GNSS-RTK (global navigation satellite system with real-time kinematic positioning), a precision satellite navigation technology. For instance, unmanned drone delivery based on GNSS-RTK data was demonstrated for pizza delivery in Korea for the first time in 2021. However, the vulnerabilities of GNSS-RTK should be overcome for delivery drones to be commercialized. In particular, jamming in the navigation system and low positioning accuracy in urban areas should be addressed. Solving these two problems can lead to stable flight, takeoff, and landing of drones in urban areas, and the corresponding solutions are expected to establish a hybrid positioning technology. We discuss current trends in hybrid positioning technology that can either replace or complement GNSS-RTK for stable drone autonomous flight.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.24 no.1
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• pp.97-110
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• 2021

Vegetation index information is an important figure that is used in many fields such as landscape architecture, urban planning, and environment. Vegetation may vary slightly in vegetation vitality depending on photosynthesis and chlorophyll content. In this study, a range of vegetation worth preserving in the Taehwa River water system was determined, and hyperspectral images of drones were acquired (August, October), and the results were presented through DVI(Normalized Defference Vegetation Index), EVI(Enhanced Vegetation Index), PRI(Photochemical Reflectance Index), ARI (Anthocyanin Reflectance Index) index analysis. In addition, field spectral data and VRS-GPS(Virtual Reference System-GPS) surveys were performed to ensure the quality and location accuracy of the spectral band. As a result of the analysis, NDVI and EVI showed low vegetation vitality in October, -0.165 and -0.085, respectively, and PRI and ARI increased to 0.011 and 7.588 in October, respectively. For general vegetation vitality, it was suggested that NDVI and EVI analysis were effectively performed, and PRI and ARI were thought to be effective in analyzing detailed characteristics of plants by spectral band. It is expected that it can be widely used for park design and landscape information modeling by using drone image information construction and vegetation information.