• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.11a
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• pp.239-240
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• 2023

Construction site management involves overseeing tasks from the construction phase to the maintenance stage, and digitalization of construction sites is necessary for digital construction site management. In this study, we aim to conduct research on object recognition at construction sites using drones. Images of construction sites captured by drones are reconstructed into BIM (Building Information Modeling) models, and objects are recognized after partially rendering the models using artificial intelligence. For the photorealistic rendering of the BIM models, both traditional filtering techniques and the generative adversarial network (GAN) model were used, while the YOLO (You Only Look Once) model was employed for object recognition. This study is expected to provide insights into the research direction of digital construction site management and help assess the potential and future value of introducing artificial intelligence in the construction industry.

• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.425-426
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• 2024

블록체인 기반 전자상거래 시스템은 탈중앙화된 P2P(Peer-to-Peer) 방식으로 데이터를 처리하고 합의 메커니즘을 통해 동기화되는 분산원장에 기록할 수 있다. 그러나, P2P 운영에 기반하여 전자상거래 과정에서 파생되는 고객의 외부 노출에 민감한 정보로 인해 고객의 개인정보가 공개되거나 유출되는 위협이 발생할 수 있다. 이에 따라, 본 논문에서는 블록체인 기반 전자상거래 시스템에서 고객의 개인정보를 보호하기 위한 PET(Privacy Enhancing Technology)를 식별하고, 블록체인 기반 전자 상거래 시스템에 적용하기 위한 방안을 분석한다.

• The Korean Journal of Air & Space Law and Policy
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• v.26 no.2
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• pp.3-39
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• 2011

People may operate unmanned aerial vehicles (UAVs or drones) thousands of miles from the drone's location. Drones were first used (like balloons) for surveillance. By 2001, the United States began arming drones with missiles and using them to strike targets during combat in Afghanistan. By mid-2010, over forty states and other entities possessed drones, many with the capability of launching missiles and dropping bombs. Each new development in military weapons technology invites assessment of the relevant international law. This Insight surveys the international law applicable to the recent innovation of weaponizing drones. In determining what international law rules govern drone use, the most salient feature is not the fact that drones are unmanned. The fact drones carry no human operator may be the most important new technological breakthrough, but the key feature for international law purposes is the type of weaponry drones carry. Whether law enforcement rules govern drone use depends on the situation and not necessarily who is operating the drone. Battlefield weapons may also be lawfully used before an armed conflict in the following situations: when initiating self-defense under Article 51 of the United Nations Charter; when authorized by the UN Security Council; when a government seeks to suppress internal armed conflict; and, perhaps, when a state is invited to assist a government in suppressing internal armed conflict. The rules governing resort to force in self-defense are found in Article 51 of the UN Charter and a number of decisions by international courts and tribunals. Commentators continue to debate whether drone technology represents the next revolution in military affairs. Regardless of the answer to that question, drones have not created a revolution in legal affairs. The current rules governing battlefield launch vehicles are adequate for regulating resort to drones. More research must be undertaken, however, to understand the psychological effects of deploying unmanned vehicles and the effects on drone operators of sustained, close visual contact with the aftermath of drone attacks.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.3
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• pp.143-149
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• 2018

Recently, due to the large-scale damage of natural disasters caused by global climate change, a monitoring system applying remote sensing technology is being constructed in disaster areas. Among remote sensing platforms, the drone has been actively used in the private sector due to recent technological developments, and has been applied in the disaster areas owing to advantages such as timeliness and economical efficiency. This paper deals with the development of a preprocessing system that can map the drone image data in a near-real time manner as a basis for constructing the disaster monitoring system using the drones. For the research purpose, our system is based on the SURF algorithm which is one of the computer vision technologies. This system aims to performs the desired correction through the feature point matching technique between reference images and shot images. The study area is selected as the lower part of the Gahwa River and the Daecheong dam basin. The former area has many characteristic points for matching whereas the latter area has a relatively low number of difference, so it is possible to effectively test whether the system can be applied in various environments. The results show that the accuracy of the geometric correction is 0.6m and 1.7m respectively, in both areas, and the processing time is about 30 seconds per 1 scene. This indicates that the applicability of this study may be high in disaster areas requiring timeliness. However, in case of no reference image or low-level accuracy, the results entail the limit of the decreased calibration.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.66-83
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• 2021

Vehicles experience changes in driving behavior due to the various facilities on the freeway. These sections may cause repetitive traffic congestion when the traffic volume increases, so safety issues may be raised. Therefore, the purpose of this study is to perform microscopic traffic analysis on these sections using drone images and to identify the causes of traffic problems. In the case of drone image, since trajectory data of individual vehicles can be obtained, empirical analysis of driving behavior is possible. The analysis section of this study was selected as the weaving section of Pangyo IC and the sag section of Seohae Bridge. First, the trajectory data was extracted through the drone image. And the microscopic traffic analysis performed on the speed, density, acceleration, and lane change through cell-unit analysis using Generalized definition method. This analysis results can be used as a basic study to identify the cause of the problem section in the freeway. Through this, we aim to improve the efficiency and convenience of traffic analysis.

• Journal of the Korea Computer Graphics Society
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• v.27 no.5
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• pp.63-71
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• 2021

Among drone autonomous flight technologies, obstacle avoidance is a very important technology that can prevent damage to drones or surrounding environments and prevent danger. Although the LiDAR sensor-based obstacle avoidance method shows relatively high accuracy and is widely used in recent studies, it has disadvantages of high unit price and limited processing capacity for visual information. Therefore, this paper proposes an obstacle avoidance algorithm for drones using camera-based PPO(Proximal Policy Optimization) reinforcement learning, which is relatively inexpensive and highly scalable using visual information. Drone, obstacles, target points, etc. are randomly located in a learning environment in the three-dimensional space, stereo images are obtained using a Unity camera, and then YOLov4Tiny object detection is performed. Next, the distance between the drone and the detected object is measured through triangulation of the stereo camera. Based on this distance, the presence or absence of obstacles is determined. Penalties are set if they are obstacles and rewards are given if they are target points. The experimennt of this method shows that a camera-based obstacle avoidance algorithm can be a sufficiently similar level of accuracy and average target point arrival time compared to a LiDAR-based obstacle avoidance algorithm, so it is highly likely to be used.

• Journal of Advanced Navigation Technology
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• v.26 no.5
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• pp.304-311
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• 2022

Although the SEAD(suppression to enemy air defenses) mission is a strategically important task in modern warfare, the high risk of direct exposure to enemy air defense assets forces to use of unmanned aerial vehicles. this paper proposes a path planning algorithm for SEAD mission for an unmanned aerial vehicle and a method for calculating the mission effectiveness on the planned path. Based on the RRT-based path planning algorithm, a low-altitude ingress/egress flight path that can consider the enemy's short-range air defense threat was generated. The Dubins path-based Intercept path planning technique was used to generate a path that is the shortest path while avoiding the enemy's short-range anti-aircraft threat as much as possible. The ingress/intercept/egress paths were connected in order. In addition, mission effectiveness consisting of fuel consumption, the survival probability, the time required to perform the mission, and the target destruction probability was calculated based on the generated path. The proposed techniques were verified through a scenario.

• Journal of the Korean Society of Safety
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• v.31 no.4
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• pp.150-155
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• 2016

This study is to suggest legislation and criteria for public service drones for disaster safety in order to enhance the research and development of the drones by helping setting right direction of the R&D. Many foreign governments are now conducting research and development on using drones as public service for disaster safety. Although there are also some efforts to using drones for public service in Korea, domestic laws and performance criteria for the drones for the purpose have not prepared yet. To set a right direction of the R&D, the laws and criteria shall be legislated and established immediately and then we can enhance the efforts to develop related technology for the drone. So this study proposed a performance criteria to fit various circumstances and situations by analyzing the aviation law in overseas. We hope this study can help R&D on the public service drones for disaster safety.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.3
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• pp.233-240
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• 2016

This paper describes a three-dimensional reference trajectory generation method for giving commands to an unmanned air vehicle (UAV). The trajectory is a set of consecutive curves with constant acceleration during each interval and passing through via-points at specified times or speeds. The functional inputs are three-dimensional positions and times (or speeds) at via-points, and velocities at both boundaries. Its output is the time series of position values satisfying the piecewise constant acceleration condition. To be specific, the shape of the trajectory, known as the path, is first represented by splines using third degree polynomials. A numeric algorithm is then suggested, which can overcome the demerits of cubic spline method and promptly generate a piecewise constant acceleration trajectory from the given path. To show the effectiveness of the present scheme, trajectory generation cases were treated, and their speed calculation errors were evaluated.

• Journal of Apiculture
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• v.34 no.4
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• pp.285-293
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• 2019

The honey bee queen shows extreme polyandry and controlling the mating partners can only be possible either by artificial insemination or having remote isolated mating locations. Here we report on the German North Sea island of Heligoland. Because of its location 60 km from the mainland, the lack of a local population of honey bees, its size of just 1.4 ㎢ and suitable weather conditions during the months of May to July, it is considered an ideal location for controlled inseminations of high-quality virgin queen bees with drones deemed genetically superior to others. Methods how to rear virgin queen bees are described and information is provided on the numbers of queen bees, their supporting workers and drone bees that are taken to the island in the mating season. The bee most commonly involved in the Heligoland mating trials has become Apis mellifera carnica strain "Baltica". In one summer, for example, 80 virgin queens (belonging to beekeepers from nine different locations in northern Germany) each with about 600 worker bees plus two drone populations of around 2,000 drones were taken by ship to Heligoland. On their return to the mainland no later than 3.5 weeks after the mating exercise, the beekeepers could register a mating success rate of 80%. This information can help operation management of the new remote mating centre of Weedo Island, Jeonbuk in Korea, which is currently under construction.