• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.1
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• pp.107-112
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• 2018

Recently, there are many real life applications that uses drones. There are various applications such as the aerial shot with the drones for the broadcasting service or drone racing competition and so on. Specifically, they patrol for the traffic enforcement on a highway. The police department use the 'Spot Mobility' method which float the drones for 30 minute period. However, this method is inefficient for the wide area with small numbers of enforcement. Therefore, a wireless network system consists of drones to patrol on the highway systematically is required. In this paper, the most efficient routing protocol will be selected for the MANET drone network by applying various routing protocols. To accomplish this, the drone patrol network system with routing protocols are designed and simulated in OPNET simulator.

• KEPCO Journal on Electric Power and Energy
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• v.4 no.2
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• pp.115-123
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• 2018

Various types of robots running on power transmission lines have been developed for the purpose of line patrol monitoring. They usually have complex mechanism to run and avoid obstacles on the power line, but nevertheless did not show satisfactory performance for going over the obstacles. Moreover, they were so heavy that they could not be easily installed on the lines. To compensate these problems, flying robots have been developed and recently, multi-copter drones with flight stability have been used in the electric power industry. The drones could be remotely controlled by human operators to monitor power distribution lines. In the case of transmission line patrol, however, transmission towers are huge and their spans are very long, and thus, it is very difficult for the pilot to control the patrol drones with the naked eye from a long distance away. This means that the risk of a drone crash onto electric power facilities always resides. In addition, there exists another danger of electromagnetic interference with the drones on autopilot waypoint tracking under ultra-high voltage environments. This paper presents a patrol monitoring plan of autopilot drones for power transmission lines and its field tests. First, the magnetic field effect on an autopilot patrol drone is investigated. Then, how to build the flight path to avoid the magnetic interference is proposed and our autopilot drone system is introduced. Finally, the effectiveness of the proposed patrol plan is confirmed through its field test results in the 154 kV, 345 kV and 765 kV transmission lines in Chungcheongnam-do.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.4
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• pp.903-921
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• 2024

Industry 5.0 puts forward higher requirements for smart cities, including low-carbon, sustainable, and people-oriented, which pose challenges to the design of smart cities. In response to the above challenges, this study introduces the cyber-physical-social system (CPSS) and parallel system theory into the design of smart cities, and constructs a smart city framework based on parallel system theory. On this basis, in order to enhance the security of smart cities, a sustainable patrol subsystem for smart cities has been established. The intelligent patrol system uses a drone platform, and the trajectory planning of the drone is a key problem that needs to be solved. Therefore, a mathematical model was established that considers various objectives, including minimizing carbon emissions, minimizing noise impact, and maximizing coverage area, while also taking into account the flight performance constraints of drones. In addition, an improved metaheuristic algorithm based on ant colony optimization (ACO) algorithm was designed for trajectory planning of patrol drones. Finally, a digital environmental map was established based on real urban scenes and simulation experiments were conducted. The results show that compared with the other three metaheuristic algorithms, the algorithm designed in this study has the best performance.

• KEPCO Journal on Electric Power and Energy
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• v.6 no.3
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• pp.271-278
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• 2020

KEPCO Research Institute developed a GIS-based autopilot drone inspection system for electric power facilities and since its pilot application in 2017, it has been successfully used to detect defects in power transmission lines. This paper presents how to operate this system in the field of power line inspection. Power transmission lines are located in a wide variety of environments such as plains, mountains, river crossings, sea crossings, and industrial areas. Among these, some transmission lines are difficult for human workers to access because of their geographies and some should be checked more often due to their severe contamination. Considering these field conditions, we classified drone operation in two categories to increase its effectiveness and efficiency - patrol surveillance and detailed inspection tasks. This paper describes the detailed procedures of the two tasks above and their field application experiences. In addition, this paper newly proposes how to construct public drone roads by using the information of KEPCO's power transmission lines.

• KEPCO Journal on Electric Power and Energy
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• v.5 no.3
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• pp.149-156
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• 2019

In the field of maintenance of power transmission lines, drones have been used for their patrol and inspection by KEPCO since 2017. This drone technology was originally developed by KEPCO Research Institute, and now workers from four regional offices of KEPCO have directly applied this technology to the drone patrol and inspection tasks. In the drone inspection system, a drone with an optical zooming camera and a thermal camera can fly automatically along the transmission lines by the ground control system developed by KEPCO Research Institute, but its camera gimbal has been remotely controlled by a field worker. Especially the drone patrol and inspection has been mainly applied for the transmission lines in the inaccessible areas such as regions with river-crossings, sea-crossings and mountains. There are often communication disruptions between the drone and its remote controller in such extreme fields of mountain areas with many barriers. This problem may cause the camera gimbal be out of control, even though the inspection drone flies along the flight path well. In addition, interference with the reception of real-time transmitted videos makes the field worker unable to operate it. To solve these problems, we have developed the auto-tracking camera gimbal system with deep learning method. The camera gimbal can track the transmission line automatically, even when the transmitted video on a remote controller is intermittently unavailable. To show the effectiveness of our camera gimbal system, its field test results will be presented in this paper.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.6
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• pp.1043-1048
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• 2017

Since year 2016, in Korea, the police department started to use drones to patrol violated vehicles on the highway area. They monitor vehicle drivers who use side ways on the highway during traffic congested hours of the season, drunken drivers, or violent drivers. They use the 'Spot Mobility' method which floats the drones for 30 minute period. However, this method is inefficient since it requires manually charging batteries, gathering data, and operate drones with many numbers of policeman. Therefore, in this paper, for the efficient patrol in this purpose, I have suggested an effectively manageable network system consists of many drones as the wireless network nodes and with small numbers of policeman in a wide highway area. To accomplish this, the two topologies of effective drone patrol network systems are designed and simulated in OPNET simulator for performance evaluation.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2016.11a
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• pp.327-329
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• 2016

본 논문에서는 최근 자주 활용되어지고 있는 드론이 경찰활동에서의 활용방안에 대해 제시하고 관련된 추가 연구과제를 도출하는데 그 목적이 있다.

• Journal of the Korea Society of Computer and Information
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• v.26 no.5
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• pp.9-16
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• 2021

In this paper, we propose a building exploration drone that can be used for a digital twin-based building control system. The existing building control system using a fixed position sensor box has a problem that a management blind spot occurs. And because people patrol themselves, it takes a lot of human resources. In this paper, a drone equipped with a temperature and humidity sensor and a gas leak detection sensor is used to search the internal path of the building centering on the control blind spot. It also aims to solve the problem of the building control system by transmitting information in real time along with the video. In addition, it has a stable hovering function using an optical floor sensor and can be applied to an existing digital twin-based building control system. The results of this study are believed to be of great help in improving the quality of digital twin control systems using drones.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.1027-1028
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• 2017

드론의 발전 속도는 빠르게 성장하고 있고, 전 세계적으로 방송 촬영, 배송, 구조, 농업분야에서 활용 범위가 확대되고 있다. 본 논문에서의 시스템은 사람이 접근하기 힘든 지역을 간단히 조립하여 수색할 수 있는 스마트 VR 드론을 통해 수색 또는 순찰에 도움이 되고자 한다. 개발된 시스템은 인력과 시간의 제약을 최소화하고, 드론을 통해 촬영한 영상을 사용자에게 가상현실을 이용한 3D영상으로 제공한다.

• Journal of Cadastre & Land InformatiX
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• v.50 no.1
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• pp.163-180
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• 2020

In this study, to build a spatial information infrastructure, which is a component of a smart city, a 3D digital twin model in the downtown area was built based on the latest spatial information acquisition technology, the drone. Several analysis models were implemented by utilizing. While the data processing time and quality of the three types of drone photogrammetry software are different, the accuracy of the construction model is ± 0.04 in the N direction and ± 0.03m in the E direction. In the m and Z directions, ± 0.02m was found to be less than 0.1m, which is defined as the allowable range of surveying performance and inspection performance for the boundary point in the area where the registration of the boundary point registration is executed. 1: 500 to 1 of the aerial survey work regulation: The standard deviation, which is the error limit of the photographic reference point of the 600 scale, appeared within 0.14 cm, and it was found that the error limit of the large scale specified in the cadastral and aerial survey was satisfied. In addition, in order to increase the usability of smart city realization using a drone-based 3D urban digital twin model, the model built in this study was used to implement Prospect right analysis, landscape analysis, Right of light analysis, patrol route analysis, and fire suppression simulation training. Compared to the existing aerial photographic survey method, it was judged that the accuracy of the naked eye reading point is more accurate (about 10cm) than the existing aerial photographic survey, and it is possible to reduce the construction cost compared to the existing aerial photographic survey at a construction area of about 30㎢ or less.