• Atmosphere
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• v.33 no.5
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• pp.441-456
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• 2023

The mobile observation method, in which a meteorological drone observes while ascending, can observe the vertical profile of wind at 1 m-interval. In addition, since continuous flights are possible at time intervals of less than 30 minutes, high-resolution observation data can be obtained both spatially and temporally. In this study, we verify the accuracy of mobile observation data from meteorological drone (drone) and fill the spatio-temporal observation gaps in the lower atmosphere. To verify the accuracy of mobile observation data observed by drone, it was compared with rawinsonde observation data. The correlation coefficients between two equipment for a wind speed and direction were 0.89 and 0.91, and the root mean square errors were 0.7 m s^-1 and 20.93°. Therefore, it was judged that the drone was suitable for observing vertical profile of the wind using mobile observation method. In addition, we attempted to resolve the observation gaps in the lower atmosphere. First, the vertical observation gaps of the wind profiler between the ground and the 150 m altitude could be resolved by wind observation data using the drone. Secondly, the temporal observation gaps between 3-hour interval in the rawinsonde was resolved through a drone observation case conducted in Taean-gun, Chungcheongnam-do on October 13, 2022. In this case, the drone mobile observation data every 30-minute intervals could observe the low-level jet more detail than the rawinsonde observation data. These results show that the mobile observation data of the drone can be used to fill the spatio-temporal observation gaps in the lower atmosphere.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.2
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• pp.176-189
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• 2024

Vertical takeoff and landing (VTOL) is a core feature of unmanned aerial vehicles (UAVs), which are commonly referred to as drones. In emerging smart logistics, drones are expected to play an increasingly important role as mobile platforms. Therefore, research on last-mile delivery using drones is on the rise. There is a growing trend toward providing drone delivery services, particularly among retailers that handle small and lightweight items. However, there is still a lack of research on a structural definition of the VTOL drone flight model for multi-point delivery service. This paper describes a VTOL drone flight route structure for a multi-drone delivery service using rotary-wing type VTOL drones. First, we briefly explore the factors to be considered when providing drone delivery services. Second, a VTOL drone flight route model is introduced using the idea of the nested graph. Based on the proposed model, we describe various time-related attributes for delivery services using drones and present corresponding calculation methods. Additionally, as an application of the drone route model and the time attributes, we comprehensively describe a simple example of the multi-drone delivery for first-come-first-served (FCFS) services.

• Electronics and Telecommunications Trends
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• v.35 no.1
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• pp.71-79
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• 2020

Since Amazon announced plans to deliver goods to customers using drones, many countries and companies have become interested in drone logistics delivery services and have begun testing drone delivery for various goods based on service scenarios. Whenever there is news of a successful drone delivery anywhere in the world, people increasingly expect the delivery of goods through drones. Although delivery services using drones are currently in a trial-and-error stage, given technical limitations and institutional and social constraints, a complete shift to drone logistics delivery is not yet possible. In anticipation of the drone logistics delivery service, recent drone delivery tests, current service trends, and requirements for drone delivery service will be examined.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2019.11a
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• pp.230-232
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• 2019

There is an accelerating need for ocean sensing where autonomous vehicles can play a key role in assisting engineers, researcher and scientists with environmental monitoring and collecting oceanographic data. This paper is performed to develops an autonomous sailing drone to be used as a sensor carrying platform for autonomous data acquisition at Sea. From a sailing drone design viewpoint, it is important to establish reliable prediction methods for sailing drone's resistance. The required power for the propulsion unit depends on the ship resistance and speed. There are three solutions for the prediction of ship resistance as follow analytical methods, model tests in tanks and Computational Fluid Dynamics (CFD). The present paper aims at simulating sailing drone friction resistance using numerical method. The dynamic mesh motion is used to describe the sailing drone movement.

• The Journal of Korea Robotics Society
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• v.12 no.4
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• pp.425-431
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• 2017

As drones gain more popularity these days, drone detection becomes more important part of the drone systems for safety, privacy, crime prevention and etc. However, existing drone detection systems are expensive and heavy so that they are only suitable for industrial or military purpose. This paper proposes a novel approach for training Convolutional Neural Networks to detect drones from images that can be used in embedded systems. Unlike previous works that consider the class probability of the image areas where the class object exists, the proposed approach takes account of all areas in the image for robust classification and object detection. Moreover, a novel loss function is proposed for the CNN to learn more effectively from limited amount of training data. The experimental results with various drone images show that the proposed approach performs efficiently in real drone detection scenarios.

• International Journal of Advanced Culture Technology
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• v.12 no.2
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• pp.286-298
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• 2024

The rapid advancement of drone technology has significantly altered the landscape of modern warfare, presenting both opportunities and challenges for military forces worldwide. As drones become increasingly sophisticated, capable of performing complex missions such as reconnaissance, surveillance, and precision strikes, the development of effective air defense systems has become a critical priority. This study examines the current state of drone and air defense technologies, analyzing their impact on military strategies, tactics, and the future battlefield environment. By exploring the patterns of technological evolution, the limitations of existing air defense systems, and the potential consequences of drone proliferation, this research highlights the need for adaptive, innovative approaches to counter emerging threats. The findings underscore the importance of investing in advanced detection and interception capabilities, developing comprehensive counter-drone doctrines, and fostering international cooperation to address the ethical and legal challenges posed by the military use of drones. As the competition between drone and air defense technologies continues to intensify, policymakers and military leaders must proactively engage in shaping the future of warfare to ensure national security and stability in an increasingly complex world.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.4_2
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• pp.1009-1017
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• 2024

In this study, technology development was promoted to enable the convergence of augmented reality technology and actual drone operation technology, and its feasibility was confirmed through implementation and performance evaluation. In addition, it is believed that the AR-based drone simulator can contribute to improving drone operation capabilities by maximizing educational effectiveness and providing a realistic training environment. Based on the results of this study, we expect to improve the quality of vocational education related to drones and achieve high educational effectiveness, and it is believed that we will be able to suggest various directions in education using augmented reality.

• The Journal of the Convergence on Culture Technology
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• v.9 no.2
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• pp.327-332
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• 2023

On December 26, 2022, North Korea's drone provocation resumed for the first time in eight years. The threat covered not only the Seoul metropolitan area but also the no-fly zone for the presidential office's security, and the South Korean military's response to it is not appropriate, which is a major controversy. In the midst of this, problems caused by the prohibition of small drones' flight and illegal intrusion into restricted areas are increasing in Korea, and the threat is becoming a reality, such as being used for terrorist attacks abroad. In this paper, the concept of "Counter-Drone" and related technologies were considered for these drone threats, and implications were derived through domestic and overseas small drone threats, and the direction of development of the Counter-Drone system was presented. North Korea's drone threat is expected to be more diversified, massified, and advanced, resulting in bolder attacks and provocations. Therefore, the South Korean military should push for early powering of the integrated control system and the conter drone system, joint and military cooperation in response to the threat of small drones, and the ability to carry out joint operations between South Korea and the U.S.

• Journal of Korea Multimedia Society
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• v.20 no.6
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• pp.927-934
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• 2017

As the technology of drone develops, the use of drone is increasing, In addition, the types of sensors that are inside of smart phones are becoming various and the accuracy is enhancing day by day. Various of researches are being progressed. Therefore, we need to control drone by using smart phone's sensors. In this paper, we propose the most suitable machine learning model that matches the gyro sensor data with drone's moving. First, we classified drone by it's moving of the gyro sensor value of 4 and 8 degree of freedom. After that, we made it to study machine learning. For the method of machine learning, we applied the One-Rule, Neural Network, Decision Tree, and Navie Bayesian. According to the result of experiment that we designated the value from gyro sensor as the attribute, we had the 97.3 percent of highest accuracy that came out from Naive Bayesian method using 2 attributes in 4 degree of freedom. On and the same, in 8 degree of freedom, Naive Bayesian method using 2 attributes showed the highest accuracy of 93.1 percent.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.26 no.2
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• pp.230-237
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• 2017

Various drones have extended application area very fast. In this paper, we define two contradictions in designing a portable-size drone by using TRIZ technique. The first is a physical contradiction between high rigidity and good portability, and the second is a technical contradiction between high stability and good portability. Through TRIZ technique, six design principles, which guide direction for optimal design, were driven. Consequently, an umbrella mechanism and design criteria were proposed for a portable-size drone. Detail design is verified through finite element method. Test results for the portable-size prototype drone show good performance, and prove its usefulness to be equivalent to a general full-size drone.