In modern international law, the absence of legal definition regarding drone(Unmanned Aerial Vehicle) has made legal scholars work on an typical analogy between aircraft codified in the international document and drone. The wording of the Convention on International Civil Aviation is limited to two categories of aircraft, such as civil aircraft and state aircraft, whereas military aircraft is not legally defined. As such it is, the current practices of the State regarding the drone flight over foreign territory have proven a hypothese that drone is being deemed as military aircraft. Principal usage of drone lies in reconnaissance and surveillance mission as well as so-called targeted killing, which is prohibited if the killing is treacherous. Claimed war against terrorism, however, is providing a legal rationale that targeted killing is not treacherous, and that the targeted person is not civilian but combatant. In such context, armed attack of drone is deemed legal and justified. Consequently, such attack is legal in the general context of the war. The rules that govern targeting do not turn on the type of weapon system used, and there is no prohibition under the laws of war on the use of technologically advanced weapons systems in armed conflict so long as they are employed in conformity with applicable laws of war. Drones may present interesting new challenges because of their sophistication and the technological advantage they convey to their operators.
Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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2016.05a
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pp.499-501
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2016
In this paper, we suggest an advance method for maintaining a perceived behavior as triangle formation and preventing collision between each other in case of a flying drone. In the existing studies, the collision of the drone is only controlled by using light entered in the camera or the image processing. However, when there is no light, it is difficult to confirm the position of each other and they can collide because this system can not confirm the each other's position. Therefore, in this paper, we propose the system to solve the problems by using the distance and the relative coordinates of the three drones that were determined using the ALPS(Ad hoc network Localized Positioning System) algorithm. This system can be a new algorithm that will prevent collisions between each other during flying the drone object. The proposed algorithm is that we make drones maintaining a determined constant value of the distance between coordinates of each drone and the measured center of the drone of triangle formation. Therefore, if the form of fixed formation is disturbed, they reset the position of the drone so as to keep the distance between each drone and the center coordinates constant. As a result of the simulation, if we use the system where the supposed algorithm is applied, we can expect that it is possible to prevent malfunction or an accident due to collisions by preventing collisions of drones in advanced behavior system.
Journal of the Korea Society of Computer and Information
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v.26
no.10
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pp.83-91
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2021
In this paper, presents an efficient education method for training specialized edutainment SW education instructors and drone realistic media creators, not just training to acquire certificates through drone manipulation training. To this end, the NCS-based curriculum was derived. The developed curriculum includes the edutainment drone curriculum and the realistic media creator curriculum. Among them, core responsibilities were defined for the drone control curriculum and core tasks, knowledge, and attitudes were described for each. After that, a detailed curriculum for drone control was derived. In the realistic media creator curriculum, pilot education was conducted to actually produce advertisement videos to foster experts who can work directly in the industrial field. Finally, through holding an online conference in a metaverse environment, a virtual conference was operated to share and discuss media videos produced by trainees. After the end of education, the efficiency of this curriculum was proved through education satisfaction analysis for 46 education graduates. This paper presented a method to achieve internalization of SW education in non-face-to-face online education that our society must solve after post-COVID-19. In addition, an efficient educational method in a realistic media environment was suggested by showing a realistic media creator training curriculum, pilot programs, and metaverse conference management cases.
Rice straw management and winter crop cultivation are crucial components for the accurate estimation of paddy methane emissions. Field-based extensive investigation of paddy organic matter management requires enormous efforts however it becomes more feasible as drone technology advances. The objectives of this study were to identify paddy fields of straw application and winter crop cultivation using drone images and to apply for the estimation of yearly methane emission. Total 35 sites of over 150ha in area were selected nationwide as the study areas. Drone images of the study sites were taken twice during summer and winter in 2018 through 2019: Summer images were used to identify paddy cultivation areas, while winter images for straw and winter crop practices. Drone-image-based identification results were used to estimate paddy methane emission and compared with conventional method. As the result, mean areas for paddy, straw application and winter crop cultivation were 118.9ha, 12.0ha, and 11.3ha, respectively. Overall rice straw application rate were greater in Gyeonggi-do(20%) and Chungcheongnam-do(12%), while winter crop cultivation was greatest in Gyeongsangnam-do(30%) and Jeolla-do(27%). Yearly mean methane emission was estimated to be 226.2kg CH4/ha/yr in this study and about 32% less when compared to 331.8kg CH4/ha/yr estimated with the conventional method. This was primarily because of the lower rice straw application rate observed in this study, which was less than quarter the rate of 55.62% used for the conventional method. This indicates the necessity to use more accurate statistics of rice straw application as well as winter crop practices into paddy methane emission estimation. Thus it is recommended to further study to link drone technology with satellite image analysis in order to identify organic management practices at a paddy field level over extensive agricultural area.
Photogrammetry using drone can produce high-resolution ortho image and acquire high-accuracy 3D information, which is useful. Therefore, this study attempted to determine the possibility of using drone-photogrammetry in park construction by producing a topographic map using drone-photogrammetry and analyzing the problems and accuracy generated during production. For this purpose, we created ortho image and DSM (digital surface model) using drone images and created topographic status map by vectorizing them. Accuracy was compared based on topographic status map by GPS (global positioning system) and TS (total station). The resulting of analyzing mean of the residuals at check points showed that 0.044 m in plane and 0.066 m in elevation, satisfying the tolerance range of 1/1,000 numerical maps, and result of compared lake size showed a difference of about 4.4%. On the other hand, it was difficult to obtain accurate height values for terrain in which existed vegetation when producing the topographic map, and in the case of underground buried objects, it is not possible to confirm it in the image, so direct spatial information acquisition was necessary. Therefore, it is judged that the topographic status map using drone photogrammetry can be efficiently constructed if direct spatial data acquisition is achieved for some terrain.
Journal of the Korea Academia-Industrial cooperation Society
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v.22
no.6
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pp.332-340
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2021
The purpose of this study was to present a method for the application of drones through analysis after surveying Jeollanam-do firefighters regarding the recognition, operation, field of application, necessary field of work, and the need for education on fire drones. As a result of the survey, 80.29% of respondents were found to be willing to operate drones, and the fields of work for which drones were considered the most necessary were in the order of rescue, fire suppression, life safety, first aid, and others. Besides, 77.38% of respondents thought that drones could contribute to the prevention of safety accidents for firefighters, and 70.13% of respondents thought that it would be appropriate to recruit firefighting drone operators through changing positions, and respondents chose firefighters in their 40s as the most suitable age group for firefighting drone operation. Also, 82.84% of respondents said they would participate in drone training, and they recognized that the use of drones could contribute to solving the physical problems caused by the aging of firefighters, and that drone training would also help firefighters manage their retirement. The fields where firefighting drones are used were investigated in the order of searching for requestors, checking on-site information, and checking on-site prior risk. In this study, a difference analysis for each group was performed according to the drone operation experience. There was a statistically significant difference in the items of safety measures for requestors. The results of variance analysis by work experience confirmed that there were statistically significant differences in a total of eight items, including four items related to the field of use of drones, and the age group of the drone operating crew, and whether or not to help retirement management.
Journal of Korea Entertainment Industry Association
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v.14
no.3
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pp.251-265
/
2020
The Drone shot is moving images captured by a remotely controlled unmanned aerial vehicle, takes usually bird's eye view. The hand-held shot is moving images recorded by literal handheld shooting which is specialized to on-the-spot filming. It takes a walker's viewpoint through vivid realism of its self-reflexive camera movements. The purpose of this study is to analyze comparatively aesthetic functions of the drone shot and the hand-held shot. For this, the study understood Certeau's concepts of 'place' and 'space,' chose World Travel 'Peninsula de Yucatan' episode as a research object, and analytically applied two concepts to the scenes clearly presenting two shots' aesthetic characteristics. As a result, the drone shot took the authoritative viewpoint providing the general information and atmosphere as it overlooked the city with silent movements removing the self-reflexivity. This aesthetic function was reinforced the narration and subtitles mediating prior-knowledge about proper rules and orders of the place. The drone shot tended to project the location as a place. Conversely, the hand-held shot practically experienced the space with free walking which is free from rules and orders inherent in the city. The aesthetics of hand-held images represented the tactic resisting against the strategy of a subject of will and power in that the hand-held shot practiced anthropological walking by means of noticing everyday lives of the small town and countryside than main tourist attraction. In opposition to the drone shot, the hand-held shot tended to reflect the location as a space.
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.
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
/
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.
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