• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.6
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• pp.124-131
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• 2017

Recently, drone is extending its range of usability. For example, the delivery, agriculture, industry, and entertainment area take advantage of drone mobilities. To control real drones, it needs huge amount of drone control training steps. However, it is risky; falling down, missing, destroying. The virtual drone system can avoid such risks. We reason that what kinds of technologies are required for building the virtual drone system. First, it needs that the virtual drone authoring tool that can assemble drones with the physical restriction in the virtual environment. We suggest that the drone assembly method that can fulfill physical restrictions in the virtual environment. Next, we introduce the virtual drone simulator that can simulate the assembled drone moves physically right in the virtual environment. The simulator produces a high quality rendering results more than 60 frames per second. In addition, we develop the physics engine based on SILS(Software in the loop simulation) framework to perform more realistic drone movement. Last, we suggest the virtual drone controller that can interact with real drone controllers which are commonly used to control real drones. Our virtual drone system earns 7.64/10.0 user satisfaction points on human test: the test is done by one hundred persons.

• Journal of Internet Computing and Services
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• v.21 no.1
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• pp.211-219
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• 2020

One of the major advancements of the Fourth Industrial Revolution is the use of Internet of Drones (IoD), which combines the Internet of Things (IoT) and drone technology. IoD technology is especially important for efficiently and economically operating C4ISR operations in actual battlefields supporting various combat situations. The purpose of this study is to solve the problems of limited battery capacity of drones and lack of budgeting criteria for military drone transcription, introduction, and operation. If the mission area is defined and corresponding multi-drone hovering check points and mission completion time limits are set, then an energy and time co-optimized scheduling and operation control scheme is needed. Because such a scheme does not exist, in this paper, a Drone Force Deployment Optimization (DFDO) scheme is proposed to help schedule multi-drone operation scheduling and networked based remote multi-drone control.

• Journal of the Korea Convergence Society
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• v.10 no.11
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• pp.125-130
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• 2019

The utilization and value of drones are increasing throughout society. However, there was a lack of government support and investment such as lack of technology of domestic drone companies, regulation of loans and lack of technology evaluation items. Therefore, this paper conducts statistical analysis to derive what drone capacity should be strengthened for the drone industry activation in Daegu. As a result, the demand satisfaction(price, quality, service) of drones leads to revitalization of drone industry when the physical, social, and policy factors among drones are strengthened. In conclusion, drone capacity to be strengthened in order to revitalize the drone industry in Korea is based on physical factors(drone demand, development, number of registrations, number of businesses and workers), social factors(national level public relations, establishment of public education institutes, correct understanding of drone occupation, preception), policy factors(privacy measures, government funding, legislation and system easing). As for the three factors, the government, industry, and drone operators are expected to have a bright future when the trinity is improved and complemented.

• Asia-Pacific Journal of Business
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• v.12 no.4
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• pp.227-240
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• 2021

Purpose - The purpose of this study is to compare and analyze the ordinances of local government in Korea to provide improvement plans for the ordinances of Drone industry. To this end, all Drone ordinances in Korea were reviewed. Design/Methodology/Approach - In this study, literature research methods were mainly used for the analysis. Furthermore, it was based on domestic laws and ordinances of local government, and preceding research data regarding government policies. Findings - Based on the analysis of domestic drone industry ordinances, the enactment of drone industry ordinances by local governments was rapidly increasing. In addition, it was urgent to enact ordinances for the use and support of drones in each region. The implication that it is necessary to subdivide the contents according to the characteristics of each region was drawn. In most of the ordinances, provisions on the basic plan and implementation plan of the drone industry could not be found. It was found that it was necessary to foster an efficient drone industry through the establishment and operation of short-term and long-term plans. Implications were drawn that it is necessary to revitalize the drone industry and expand the drone use industry. Research Implications or Originality - This paper suggest the establish an ordinance for utilizing and supporting Drone industry. Additionally, establishment of suitable ordinance for regional characteristics is needed. In future research, detailed data on Yeongwol's Drone industry based on survey should be derived. Moreover, the development plan and implication for drone industry should be derived through analysis of the survey data.

• International Journal of Internet, Broadcasting and Communication
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• v.9 no.4
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• pp.31-37
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• 2017

Recently Drone technology is emerging as an alternative new way of distribution systems services. Amazon, Google which are global network chain distribution companies are developing an idea of Drone based delivery service and applied for patent for Drone distribution systems in USA. In this paper, we investigate a way to adopt Drone system to Air Cargo logistics, in particular, drone system based on combination of Light ID and RFID technology in the management procedure in stock warehouse. Also we explain the expected impact of Drone systems to customs declaration process. In this paper, we address the investigated limitations of Drone by the Korean Aviation Act as well as suggest the directions of future research for application of Drone to Air logistics industry with investigated limitations.

• Journal of Korea Game Society
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• v.18 no.3
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• pp.113-122
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• 2018

In this paper, we will discuss planning and production of VR contents for effective racing drone steering training. In the real world, direct racing drone training training is obviously a space and economic limit. We propose through the production of VR-based drone infiltration action game as a solution to these limitations and try to improve effective drone handling ability. Especially, we designed the virtual reality contents in a similar environment by using the similarity of FPV goggles and HMD based VR, and designed virtual drones, maps and obstacles considering the characteristics of the structures used in racing drone and drone racing. Also, we tried to increase the user's immersion and presence by increasing difficulty level of obstacles.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.6
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• pp.289-296
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• 2018

Drone detection in FMCW radar system needs complex techniques because a drone beat frequency is highly dynamic and unpredictable. Therefore, the current static signal processing algorithms cannot show appropriate detection accuracy. With dynamic signal fluctuation and environmental clutters, it can fail to detect a drone or make false detection. It affects to the radar system integrity and safety. Constant false alarm rate (CFAR), one of famous static signal process algorithm is effective for static environment. But for drone detection, it shows low detection accuracy. In this paper, we suggest neural network based FMCW radar system for detecting a drone. We use recurrent neural network (RNN) because it is the effective neural network for signal processing. In our FMCW radar system, one transmitter emits FMCW signal and four-way fixed receivers detect reflected drone beat frequency. The coordinate of the drone can be calculated with four receivers information by triangulation. Therefore, RNN only learns and inferences reflected drone beat frequency. It helps higher learning and detection accuracy. With several drone flight experiments, RNN shows false detection rate and detection accuracy as 21.1% and 96.4%, respectively.

• Journal of Platform Technology
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• v.9 no.3
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• pp.78-83
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• 2021

The new industry drone research is increasing through convergence between 4th industrial revolution technology. In particular, the government indicates the D.N.A platform as a countermeasure of 4th industrial revolution. So, the research topics are remarkable which are using D.N.A platform. On the other hand, the drone for industrial and research has spatial factor based on sequential because, they performance scenario-based mission through control operation. When the drone flights as a control operation, they have necessity apply multi-dimensional methods to improve the security level. So, this study researched a scenario based drone platform to improve the security level. As a result, the space classified as a ground control system, drone, drone data server and designed the application method based on scenario security technology.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.664-666
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• 2021

Anti-drone means a device that detects and blocks the intrusion and activity of illegal drones, and includes technology that crashes illegal drones or destroys them in the air. This paper analyzes the impact of jamming due to remote drone detection with anti-drone technology. The impact of jamming signals may vary depending on the distance of the drone. The present invention has an advantage of simultaneously jamming a drone at a short distance and a drone at a long distance due to the generation of a triangular wave, and efficiently operates a battery by not transmitting the drone at a maximum power.Also, even if the jamming is not affected at a distance, the jamming effect is greater at a close range, so it can be influenced differently.

• Journal of the Korean Society of Systems Engineering
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• v.19 no.2
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• pp.126-134
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• 2023

Drones are emerging as a new security threat, and the world is working to reduce them. Detection and identification are the most difficult and important parts of the anti-drone systems. Existing detection and identification methods each have their strengths and weaknesses, so complementary operations are required. Detection and identification performance in anti-drone systems can be improved through the use of artificial intelligence. This is because artificial intelligence can quickly analyze differences smaller than humans. There are three ways to utilize artificial intelligence. Through reinforcement learning-based physical control, noise and blur generated when the optical camera tracks the drone may be reduced, and tracking stability may be improved. The latest NeRF algorithm can be used to solve the problem of lack of enemy drone data. It is necessary to build a data network to utilize artificial intelligence. Through this, data can be efficiently collected and managed. In addition, model performance can be improved by regularly generating artificial intelligence learning data.