• KIPS Transactions on Computer and Communication Systems
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• v.8 no.12
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• pp.277-286
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• 2019

The Unmanned Aerial Vehicle (UAV) is one of the most precious inventions of Internet of things (IOT). UAV faces the necessity to charge battery or replace battery from the charging stations during or between services. We propose scheduling algorithms for drone power charging (SADPC). The basic idea of algorithm is considering both a deadline (for increasing deadline miss ratio) and a charging time (for decreasing waiting time) to decide priority on charging station among drones. Our simulation results show that our power charging algorithm for drones are efficient in terms of the deadline miss ratio as well as the waiting time in general in compare to other conventional algorithms (EDF or SJF). Also, we can choose proper algorithms for battery charge scheduling and charge ready battery allocation according to system parameters and user requirements based on our simulation.

• Journal of Convergence for Information Technology
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• v.9 no.10
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• pp.101-107
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• 2019

This paper proposes a method for detecting faults in conveyor systems used for transportation of raw materials needed in the thermal power plant and cement industries. A small drone was designed in consideration of the difficulty in accessing the industrial site and the need to use it in wide industrial site. In order to apply the system to the embedded microprocessor, hardware and algorithms considering limited memory and execution time have been proposed. At this time, the failure determination method measures the peak frequency through the measurement, detects the continuity of the high frequency, and performs the failure diagnosis with the high frequency components of noise. The proposed system consists of experimental environment based on the data obtained from the actual thermal power plant, and it is confirmed that the proposed system is useful by conducting virtual environment experiments with the drone designed system. In the future, further research is needed to improve the drone's flight stability and to improve discrimination performance by using more intelligent methods of fault frequency.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.12
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• pp.997-1004
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• 2020

A synchropter is a type of rotorcraft in which a pair of blades inclined with each other rotates in synchronization. Removing the tail rotor enables an efficient and compact configuration similar to a coaxial-rotor helicopter. This paper describes the design and flight test results of a small synchropter to examine the suitability of a drone system for the army. The synchropter in this paper is a small vehicle with a rotor diameter of 1.4m and a weight of 7kg and was assembled based on commercial parts to examine flight characteristics effectively. The flight control system adopted Pixhawk, which is designed based on an open-architecture. The model-based design technique is applied to develop the control law of the synchropter and a new firmware embedded on the Pixhawk. Through qualitative flight tests, we analyzed the flight characteristics. As a result of the analysis, we confirmed the possibility of application as a drone system of the synchropter.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.381-382
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• 2019

본논문에서는 산업용 드론개발을 위한 안정성 향상에 대하여 연구하였다. 기존의 비행체의 경우 고신뢰도 대용량의 제어시스템을 이용하여 비행제어시스템을 구성하지만 무인 비행체는 소형 내장형시스템을 이용한다. 본 연구에서는 소형 무인 비행체에서 사용하는 소형 내장형 비행제어시스템에서 안정성을 개선하기 위한 방법으로 비행제어신호와 모터의 제어신호를 측정하여 안정상태와 이상상태를 구별한다. 제안한 방법은 기존의 비행제어시스템을 수정하지 않고 비행제어시스템의 감시가 가능 할 것으로 예상한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.1065-1067
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• 2022

울산항에서 일어나는 선박사고를 줄이고자 실제 산업환경정보를 수집하여 관제서버로 전송할 수 있는 기능을 갖춘 수상드론과 소형선박 운항자들을 대상으로 제작된 메타환경에서의 모의 운항을 할 수 있는 시뮬레이터를 제작하여 안전한 산업환경을 만들기 위해 복합적인 항만 안전운항관리 솔루션을 구축하고자 한다.

• Korean Journal of Remote Sensing
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• v.35 no.5_2
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• pp.841-850
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• 2019

The purpose of this study is to strengthen the capability of rapid mapping for disaster through improving the positioning accuracy of mapping and fusion of multi-sensing point cloud data derived from Unmanned Aerial Vehicles (UAVs) and disaster investigation vehicle. The positioning accuracy was evaluated for two procedures of drone mapping with Agisoft PhotoScan: 1) general geo-referencing by self-calibration, 2) proposed geo-referencing with optimized camera model by using fixed accurate Interior Orientation Parameters (IOPs) derived from indoor camera calibration test and bundle adjustment. The analysis result of positioning accuracy showed that positioning RMS error was improved 2~3 m to 0.11~0.28 m in horizontal and 2.85 m to 0.45 m in vertical accuracy, respectively. In addition, proposed data fusion approach of multi-sensing point cloud with the constraints of the height showed that the point matching error was greatly reduced under about 0.07 m. Accordingly, our proposed data fusion approach will enable us to generate effectively and timelinessly ortho-imagery and high-resolution three dimensional geographic data for national disaster management in the future.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.6
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• pp.874-880
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• 2018

3D modeling is extensively used in the field of architecture, machinery and contents production such as movies. Modeling is a time-consuming task. In order to compensate for these drawbacks, attempts have recently been made to reduce the production period by applying 3D scanning technology. 3D scanning for small objects can be done directly with laser or optics, but large buildings and sculptures require expensive equipment, which makes it difficult to acquire data directly. In this study, 3D modeling data for a large object is acquired using photometry with using drones to acquire the image data. The maintenance method for uniform spacing between the sculpture and the drone, the measurement method for the flight line were presented. In addition, we presented a production environment that can utilize the obtained 3D point cloud data for animation and a rendered animation result to find ways to make it in various environments.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.9
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• pp.774-781
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• 2018

In this investigation, a gas gun is proposed driven by carbon dioxide gas and installed on a quadcopter-type small unmanned drone for the purpose of cattle vaccination, and we developed a launcher and its connection unit. The system consists of a commercial drone, a gas gun, a solenoid valve, and the remote communication controller, etc. The velocity of launched projectile is measured, and the full system is finally validated through ground test and flight examination loaded for the real aircraft. The feasibility is checked if this technology is applicable to various disease abatement and hazard mitigation in the fields of agriculture and fire-fighting with the present research and development.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.29 no.3
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• pp.162-168
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• 2017

Shallow-water bathymetry survey has been conducted using high definition color images obtained at the altitude of 100 m above sea level using a drone. Shallow-water bathymetry data are one of the most important input data for the research of beach erosion problems. Especially, accurate bathymetry data within closure depth are critically important, because most of the interesting phenomena occur in the surf zone. However, it is extremely difficult to obtain accurate bathymetry data due to wave-induced currents and breaking waves in this region. Therefore, optical remote sensing technique using a small drone is considered to be attractive alternative. This paper presents the potential utilization of image processing algorithms using multi-variable linear regression applied to red, green, blue and grey band images for estimating shallow water depth using a drone with HD camera. Optical remote sensing analysis conducted at Wolpo beach showed promising results. Estimated water depths within 5 m showed correlation coefficient of 0.99 and maximum error of 0.2 m compared with water depth surveyed through manual as well as ship-board echo-sounder measurements.

• Journal of Cadastre & Land InformatiX
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• v.53 no.2
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• pp.5-18
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• 2023

As the development of drones and sensors accelerates, new services and values are created by fusing data acquired from various sensors mounted on drone. However, the construction of spatial information through data fusion is mainly constructed depending on the image, and the quality of data is determined according to the specification and performance of the hardware. In addition, it is difficult to utilize it in the actual field because expensive equipment is required to construct spatial information of high-quality. In this study, super-resolution was performed by applying deep learning to low-resolution images acquired through RGB and THM cameras mounted on a drone, and quantitative evaluation and feature point extraction were performed on the generated high-resolution images. As a result of the experiment, the high-resolution image generated by super-resolution was maintained the characteristics of the original image, and as the resolution was improved, more features could be extracted compared to the original image. Therefore, when generating a high-resolution image by applying a low-resolution image to an super-resolution deep learning model, it is judged to be a new method to construct spatial information of high-quality without being restricted by hardware.