• Journal of the Society of Disaster Information
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• v.19 no.2
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• pp.395-410
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• 2023

Purpose: The purpose of this study was to analyze the current state of drone terrorism response at such critical national facilities and derive improvements, especially to identify problems in laws and systems to effectively utilize the anti-drone system and present directions for improvement. Method: A qualitative research method was used for this study by analyzing a variety of issues not discussed in existing research papers and policy documents through in-depth interviews with subject matter experts. In-depth interviews were conducted based on 12 semi-structured interviews by selecting 16 experts in the field of anti-drone and terrorism in Korea. The interview contents were recorded with the prior consent of the study participants, transcribed back to the Korean file, and problems and improvement measures were derived through coding. For this, the threats and types were analyzed based on the cases of drone terrorism occurring abroad and measures to establish anti-drone system were researched from the perspective of laws and systems by evaluating the possibility of drone terrorism in the Republic of Korea. Result: As a result of the study, improvements to some of the problems that need to be preceded in order to effectively respond to drone terrorism at critical national facilities in the Republic of Korea, have been identified. First, terminologies related to critical national facilities and drone terrorism should be clearly defined and reflected in the Integrated Defense Act and the Terrorism Prevention Act. Second, the current concept of protection of critical national facilities should evolve from the current ground-oriented protection to a three-dimensional protection concept that considers air threats and the Integrated Defense Act should reflect a plan to effectively install the anti-drone system that can materialize the concept. Third, a special law against flying over critical national facilities should be enacted. To this end, legislation should be enacted to expand designated facilities subject to flight restrictions while minimizing the range of no fly zone, but the law should be revised so that the two wings of "drone industry development" and "protection of critical national facilities" can develop in a balanced manner. Fourth, illegal flight response system and related systems should be improved and reestablished. For example, it is necessary to prepare a unified manual for general matters, but thorough preparation should be made by customizing it according to the characteristics of each facility, expanding professional manpower, and enhancing response training. Conclusion: The focus of this study is to present directions for policy and technology development to establish an anti-drone system that can effectively respond to drone terrorism and illegal drones at critical national facilities going forward.

• The Journal of the Convergence on Culture Technology
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• v.5 no.3
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• pp.257-262
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• 2019

Recently, with a great deal of attention and utilization to the UAV like a drone, many application cases using UAV in various fields have been proliferated rapidly. These UAV, however, has many risks like balance deviation and drone crash due to the external environmental factors. The attitude control algorithm for UAV is the most important portion in order to maintain the safe management of UAV, and the best solution is PID control algorithm which is generously used and almost perfect attitude control technology nowadays. In this paper, we propose the smart attitude control algorithm using fuzzy logic in order to provide safe and continuous attitude control against external environmental factors, and compare the performance through simulation study between PID and our algorithm.

• Journal of the Korea Society of Computer and Information
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• v.27 no.4
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• pp.53-60
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• 2022

Recently, as the amount of data collected by drones has rapidly increased, it is necessary to support cloud computing technology that can securely and efficiently store and process data. However, various security threats such as stealing, leaking, or tampering with data communicated by drones can occur due to attackers. Therefore, there is a need for security technology to provide secure communication of data collected from drones. Among various security technologies, the KP-ABE scheme, which is attribute-based encryption, is a security technology that satisfies two characteristics: data encryption and user access control. This paper researched the KP-ABE scheme and proposed a secure data access control scheme to the drone environment. This proposed scheme provides confidentiality and integrity of data communicated in a drone environment and secure access control and availability. In addition, it provides a fast ciphertext search and constant size ciphertext among the requirements to be provided in the KP-ABE scheme.

• Journal of Advanced Navigation Technology
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• v.27 no.2
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• pp.209-213
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• 2023

Currently, 2.4 GHz and 5 GHz bands are used as frequencies for drone operation. In December 2019, the Ministry of Science and ICT newly allocated the 433 MHz band for the invisible long-distance operation of drones. However, since the 433 MHz band is the same as the previously allocated frequency band for amateur radio communication, interference cannot be avoided. Therefore, as a prerequisite for the development of a drone operation system based on the 433 MHz band, interference avoidance technology for this frequency band must be developed and applied. In this paper, we report the results of measurement and analysis of 433 MHz band signals necessary for the development of interference avoidance and reduction technologies for 433 MHz signals. The measurement and analysis of the 433 MHz band signal are performed through the spectrum measured at 5-minute intervals at three locations. Since the measurements and analyzes performed in this study considered spatial characteristics, temporal characteristics, and traffic characteristics, it is considered to be the basic data necessary for the development of interference avoidance technology in the 433 MHz band.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.263-270
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• 2023

The Ukraine-Russia war is a testing ground for High-Tech weapons and the first full-scale drone warfare. The Ukrainian military has been aggressively deploying a variety of reconnaissance and attack drones on the battlefield, and more recently, FPV drones, also known as racing drones, have been fitted with bombs as a game-changer in small-unit combat. To better understand these FPV drones, this article reviews their definition, aircraft components, and key characteristics, and draws implications from the Ukrainian military's FPV combat experience. In the future, the combination of artificial intelligence and swarming technology will make FPV drones even more lethal. Accordingly, the need to develop FPV drones suitable for the future operational environment on the Korean Peninsula is increasing, and follow-up research is needed to specify fighting methods and optimize related technologies.

• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.425-430
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• 2024

This paper analyzes the characteristics of various types of unmanned aerial vehicles (drones) for military use and how each type can be utilized in military operations. The scope of the study focuses on the structural features, advantages and disadvantages, and military application cases of fixed-wing, rotary-wing, hybrid, and swarm drones. It also discusses the development direction of drone technology, changes in military strategy, opportunities, and challenges. The results show that each type of drone plays a crucial role in various military operations such as reconnaissance, surveillance, strike, logistics, search, and rescue. With advancements in artificial intelligence, autonomous flight, and swarm technologies, the range of drone applications is expected to expand further. However, ensuring the safety and ethics of drone operations and establishing international norms have emerged as major challenges.

• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.413-418
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• 2024

This paper analyzes the technological advancements of military drones and their subsequent effects on modern warfare and international relations. It first examines the historical development of military drones and analyzes the key features and advantages of contemporary military drones. The paper then explores the changes in warfare tactics and military strategies brought about by drone technology, along with discussing the legal and ethical issues related to drone usage. Finally, recent war cases and country-specific responses are reviewed to evaluate the current operational status and impact of military drones. This study offers recommendations for the development of drone operations within the South Korean military and addresses the legal and ethical challenges posed by drone warfare on the international stage.

• Aerospace Engineering and Technology
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• v.4 no.2
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• pp.7-14
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• 2005

This paper describes development of automatic flight control system for an unmanned target drone. Current target drone is operated by pilot control of on-board servo motor via remote control system. Automatic flight control system for the target drone greatly reduces work load of ground pilot and can increase application area of the drone. Most UAVs being operated nowdays use high-priced sensors as AHRS and IMU to measure the attitude, but those are costly. This paper introduces the development of low-cost automatic flight control system with low-cost sensors. The integrated automatic flight control system has been developed. The performance of automatic flight control system is verified by flight test.

• Corrosion Science and Technology
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• v.18 no.6
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• pp.253-257
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• 2019

A deep learning based real-time painting surface inspection algorithm is proposed herein, designed for developing an autonomous inspection drone. The painting surface inspection is usually conducted manually. However, the manual inspection has a limitation in obtaining accurate data for correct judgement on the surface because of human error and deviation of individual inspection experiences. The best method to replace manual surface inspection is the vision-based inspection method with a camera, using various image processing algorithms. Nevertheless, the visual inspection is difficult to apply to surface inspection due to diverse appearances of material, hue, and lightning effects. To overcome technical limitations, a deep learning-based pattern recognition algorithm is proposed, which is specialized for painting surface inspections. The proposed algorithm functions in real time on the embedded board mounted on an autonomous inspection drone. The inspection results data are stored in the database and used for training the deep learning algorithm to improve performance. The various experiments for pre-inspection of painting processes are performed to verify real-time performance of the proposed deep learning algorithm.

• Journal of Satellite, Information and Communications
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• v.12 no.4
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• pp.157-161
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• 2017

Effective management of ULD (Unit Load Device) in Air Cargo Transportation is one of the Airline's main concerns. At present, the way of management of ULD which has the ID tag based on RFID is carried by cargo control staff with PDA. However, the activity of ULD management is limitted due to complexity of cargo terminal facilities. In this study, we offer the effective way of management of ULD by the DRONE equipped by LED-ID & RFID READER at the higher altitude in Air Cargo Terminal to recover the difficulty of identification due to complexity of terminal facilities. Further to the above, we suggest the operational effectiveness, limitation, and the direction of future research.