• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.3
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• pp.31-36
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• 2022

Recently, drones are being used in various fields, and drone technology is also developing. The risks of drones are increasing, then technology to detect drones is important. However, it is extremely difficult to detect and recognize drones due to the low level radar cross section of the commercial drones. In this paper, a signal processor structure that was mounted the miniaturized and light-weighted was designed. in order to process large amounts of data in real time, parallel processing was performed for each channel and an algorithm was applied to shorten the operation time in each step. As a test of verifing the detection performance through test, it was confirmed that the structure design works in real time.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.225-226
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• 2021

드론산업과 센서의 발전에 따라 드론이 수행할 수 있는 능력이 넓어지고 있다. 본 논문에서는 드론에 장착되는 장비 중 카메라에 객체 탐지 기능을 넣어 퇴치할 대상을 인지하고 인식할 수 있음을 검증하고자한다. 이는 여러 산업에 새로운 패러다임을 제안하게 될 수 있는 방법이 될 것 이라 기대된다.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.6
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• pp.601-608
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• 2017

In the fourth industrial revolution, drones are an important element to lead the industry by converging with information technology. Drones are developing various technologies by combining with communication / navigation / traffic management technology, control and detection / avoidance technology, sensor technology, SW and application technology. However, there are various problems in order to settle the drone technology. In this paper, it will be examined the problems of application of drones through application fields of drones, domestic and foreign cases, and core technologies of drones. The growth of the drone market requires improvement of laws and institutions. This paper proposed security vulnerability, privacy and safety problem in wireless communication, and present technical and management problems for drone service in the Korean environment in particular.

• Electronics and Telecommunications Trends
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• v.33 no.3
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• pp.78-88
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• 2018

As the unmanned aerial vehicle industry and its related technologies grow each year, the number of abuse cases caused by drones is increasing. In addition to the invasion of privacy caused by indiscriminate photography, terrorism using unmanned aerial vehicles, which have a low detection probability, high location accuracy, and the capability of targeting people or places, as well as carrying chemicals, radiation materials, and small bombs, is becoming a significant problem around the world. Accordingly, many companies are developing anti-drone solutions that consist of various technologies such as radar, EO/IR cameras, and RF jammers to detect and disable unmanned aerial vehicles. This article briefly introduces the recent R&D trends and technical levels of anti-drone technologies.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.303-304
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• 2019

본 논문에서는 자연재해나 노후화로 인해 많은 건물의 외벽에 균열(Crack)이 생기고 있고, YOLO 딥러닝 기법을 이용하여 텐서플로우(Tensorflow)기반 균열 데이터의 학습 과정을 거쳐 가중치 파일을 획득하고, 이를 기반으로 효율적으로 건물 관리를 할 수 있는 드론(Drone)에 장착된 카메라를 이용한 실시간 영상으로 건물 외벽 균열을 촬영하고 균열을 감지하여 사용자 모니터에 감지된 균열을 경계 상자를 통해 검출하고, 검출 사진과 위치를 기록하도록 시스템을 개발하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.213-216
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• 2022

There has been an increase in video surveillance for public safety and security, which increases the video data, leading to analysis, and storage issues. Furthermore, most surveillance videos contain an empty frame of hours of video footage; thus, extracting useful information is crucial. The prominent framework used in surveillance for efficient storage and analysis is video synopsis. However, the existing video synopsis procedure is not applicable for creating an abnormal object-based synopsis. Therefore, we proposed a lightweight synopsis methodology that initially detects and extracts abnormal foreground objects and their respective backgrounds, which is stitched to construct a synopsis.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.688-689
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• 2022

This paper proposes the development of an AI drone equipped with motion detection and thermal imaging camera to quickly rescue people from drowning accidents. Currently, when a drowning accident occurs, a large number of manpower must be put in to find the person who needs it, such as conducting a search operation. The time required for this process is too long, and especially the night search is more difficult for a person to do directly. To solve this situation, we are going to use AI drones.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.5
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• pp.592-597
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• 2020

Currently, river survey data is mainly performed by acquiring longitudinal and cross-sectional data of rivers using total stations or the GNSS(Global Navigation Satellite System). There is not much research that addresses the use of LiDAR(Light Detection and Ranging)systems for surveying rivers. This study evaluates the applicability of using LiDAR data for surveying rivers The Ministry of Land, Infrastructure and Transport recently launched a drone-based river fluctuation survey. Pilot survey projects were conducted in major rivers nationwide. Studies related to river surveying were performed using the ground LiDAR(Light Detection And Ranging)system.Accuracy was ensured by extracting the linearity of the object and comparing it with the total station survey performance. Data on trees and other features were extracted to generate three-dimensional geospatial information for the point-cloud data on the ground.Deviations were 0.008~0.048m. and compared with the results of surveying GNSS and the use of drone LiDAR data. Drone LiDAR provided accurate three-dimensional spatial information on the entire target area. It was able to reduce the shaded area caused by the lack of surveying results of the target area. Analyses such as those of area and slope of the target sites are possible. Uses of drones may therefore be anticipated for terrain analyses in the future.

• Journal of Broadcast Engineering
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• v.24 no.2
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• pp.243-250
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• 2019

In this paper, we propose a system for processing and analyzing drone image information which can be applied variously in disasters-security situation. The proposed system stores the images acquired from the drones in the server, and performs image processing and analysis according to various scenarios. According to each mission, deep-learning method is used to construct an image analysis system in the images acquired by the drone. Experiments confirm that it can be applied to traffic volume measurement, suspect and vehicle tracking, survivor identification and maritime missions.

• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.33-40
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• 2022

In this paper, we propose a system that analyzes drone photographic images of panel-type factory roofs and conducts abnormal detection of bolts. Currently, inspectors directly climb onto the roof to carry out the inspection. However, safety accidents caused by working conditions at high places are continuously occurring, and new alternatives are needed. In response, the results of drone photography, which has recently emerged as an alternative to the dangerous environment inspection plan, will be easily inspected by finding the location of abnormal bolts using deep learning. The system proposed in this study proceeds with scanning the captured drone image using a sample image for the situation where the bolt cap is released. Furthermore, the scanned position is discriminated by using AI, and the presence/absence of the bolt abnormality is accurately discriminated. The AI used in this study showed 99% accuracy in test results based on VGGNet.