해상특수교량은 특수한 환경적 조건뿐 아니라 고주탑의 구조형식, 보호재로 쌓여있는 케이블 등 특 수한 형식을 가지고 있어 일반적인 육안전검으로 안전점검을 할 수 없는 사각지대가 존재한다. 주탑의 외부 손상상태 및 케이블의 손상에 대해서는 정밀안전점검에서도 점검이 되지 않는 경우가 대부분이 므로 이에 대한 대책 마련이 시급하다. 또한 해상특수교량에 대한 전문적인 경험과 기술이 부족한 관 리자도 대상교량의 손상과 이상거동을 직관적으로 확인하고 판단할 수 있는 지원체계가 필요하다. 이 에 본 연구에서는 해상특수교량 고주탑에 대한 손상정보를 파악하기 위하여 드론의 자동비행 기술을 개발하고 이를 이용하여 주탑 외부 균열 손상에 대한 안전점검을 실시하고 이를 분석하였다.

도로의 포장 상태의 노후화나 관리미흡으로 인하여 시민의 사유 재산 중 주요한 요소인 자동차 등의 손상이나 자동차 사고 로 이어질 수 있어 큰 사회적 비용이 발생할 뿐 아니라, 시민들의 불편과 불만을 초래할 수 있다. 최근 도로 포장의 경우 포트홀 발생 건수와 그에 따른 민원 및 소송 건수가 증가해 행정력 및 예산이 낭비되고 있으며, 서울시의 경우 포장도로 노후화 추이가 증가함에 따라 유 지 관리 비용 또한 증가하고 있다. SOC 시설물 안전성 강화에 대한 사회적 요구는 지속적으로 증가하고 있어 한정된 예산의 효율적 활용을 위한 첨단 유지관리기술 도입이 시급하다.

In recent times, drone technology has been rapidly advancing and becoming increasingly popular. Furthermore, there has been an increase in the number of crimes and terrorism cases targeting national facilities using drones. This study aims to categorize the types of drone threats that could pose future risks to nuclear power plants. For this study, we are investigating domestic and foreign drone terrorism cases and identifying the specifications of drones used. It has been confirmed that products from Chinese DJI companies have frequently appeared as commercial drones used in terrorism. This suggests that conversion of general commercial drones into weapons can be effectively utilized for terrorist activities. There is an elevated risk of terrorism involving multiple small drones. Nuclear power plants must also devise protective measures against a large influx of drones. Additionally, it is predicted that North Korea is developing drones equipped with return technology through GPS-based autonomous mission flights. North Korea’s drones are presumed to have been converted from Chinese drones (SKY-09P, UV10CAM, etc.). According to the analysis based on the weight and size of the drone, drones weighting less than 150 kg and wingspan of less than 3 m are used for terrorism. To effectively detect drones, it is necessary to implement measures such as integrating and deploying various equipment to compensate for equipment limitations (radio waves, radar, video, sound, etc.). In the case of long-distance flight, a number of fixed-wing drones capable of autonomous mission flight and long-distance flight were used. North Korea’s drones use GPS-based autonomous mission flights, so it is necessary to prepare drones that do not transmit RF signals to detect them. Both RF signal detection and GPS jamming should be carried out, with GPS jamming taking precedence, even in the case of fixedwing drones. The results of this study could contribute to enhancing the level of physical protection of nuclear power plants.

As drones expand beyond military purposes to the private sector, the level of use of drones in various fields is increasing. However, the world was shocked by the attempt to attack with a drone equipped with a C4 bomb in the US and the attempt to assassinate a head of state using a drone in Venezuela. Drone threats to domestic nuclear power plants are also increasing due to the expansion of drone use, terrorist threats, and North Korea’s invasion of drones. Overseas, various drone threats to nuclear power plants have occurred. In October 2014, French electricity company Electricite de France confirmed that it had observed unauthorized drones over seven nuclear power plants across France. A drone threat occurred at the Savannah River Site (SRS), a U.S. Department of Energy facility that processes and stores nuclear materials. In 2016, eight drones were observed by security personnel. In 2016, a drone flew over the cooling tower of the Liebstadt nuclear power plant in Switzerland, and publicly shared the filmed video on YouTube. In July 2018, Greenpeace activists intentionally crashed a drone into the outer wall of the spent fuel building in Boughey, France. In January 2019, they used drones to drop smoke bombs and release videos at Orangeo’s nuclear facility containing irradiated fuel. In January 22, Sweden saw drones flying over three nuclear power plants. Drone was also seen at the Forsmark nuclear power plant on Friday and at two other Swedish nuclear power plants in Oskarshamn and Ringhals on Monday. Anti-drone technology to counter the threat of drone terrorism is also developing. Anti-drone technology detects, tracks, and identifies illegal drones to neutralize them. Various technologies such as radar, EO/IR cameras, Lidar, sensor, and RF scanners are being developed for drone detection. Depending on the detection technology, it has advantages such as detection distance and remote control drone detection. However, there are also disadvantages, such as obstacles, weather condition, and the inability to detect drones that do not transmit signals. Methods such as jammer, capture, and destruction have been developed for incapacitation technology. While it has advantages such as stability and portability, it has disadvantages such as limited use and damage to the surroundings. Accordingly, it is necessary to draw realistic measures to defend against the threat of nuclear power plants by paying constant attention to the various detection, identification, and neutralization anti-drone systems that continue to evolve.

본 연구는 벼 화분에 잔류한 네오니코티노이드계 약제가 꿀벌 봉군 내로 유입하여 만성적으로 피해를 주는지 에 대해 실험적으로 검증하고자 한다. 벼 꽃 개화기에 맞춰 논 인근의 세 지역에 각 6개 봉군을 설치하였다. 3개의 지역 중 두 지역은 벼 꽃 개화기 항공 방제 수행지역이고, 1개 지역은 미수행 지역이다. 지역마다 봉군 3개에는 채분기를 설치하여 벌통 내 화분 유입을 차단한 그룹과 미설치 그룹 간 봉세와 꿀벌 면역 및 수명 관련 유전자 발현량을 비교하였다. 약제 방제가 수행된 지역에서 채분기를 설치한 봉군의 봉세는 미설치 봉군보다 상대적으 로 강한 것을 확인하였다. 또한, 약제 처리 지역에서 채분기 설치 봉군에서 채분기를 설치한 봉군의 봉세는 미설치 봉군보다 상대적으로 강한 것을 확인하였다. 또한, 약제 처리 지역에서 채분기 설치 봉군에서 채집된 꿀벌의 면역 및 수명 관련 유전자 발현량이 미설치 그룹과 차이가 있는 것을 확인하였다.

This study examines and proposes standardization approaches to address the heterogeneous issues of metadata in drone imagery within the agricultural sector. Image metadata comes in various formats depending on different camera manufacturers, with most utilizing EXIF and XMP. The metadata of cameras used in fixed-wing and rotary-wing platforms, along with the metadata requirements in image alignment software, were analyzed for sensors like DJI XT2, MicaSense RedEdge-M, and Sentera Double4K. In the agricultural domain, multispectral imagery is crucial for vegetation analysis, making the provision of such imagery essential. Based on Pix4D SW, a comparative analysis of metadata attributes was performed, and necessary elements were compiled and presented as a proposed standardization (draft) in the form of tag information.

At a time when the demand for drones is increasing, a plan to utilize drone images was sought for efficient promotion of cadastral resurvey. To achieve the purpose of this study, the technical and legal status of drone images was reviewed, and through this, the possibility of using it for cadastral resurvey was primarily reviewed. subsequently, an experiment was conducted targeting the project district to examine whether drone images were applied to boundary extraction, which is the primary process of cadastral resurvey. As a result of the experiment, it was found that boundary extraction from images is possible. However, in some cases, it is impossible due to field conditions or image quality. Therefore, it is necessary first to apply cases where boundary extraction is possible to cadastral resurvey and seek solutions for some impossible cases. In particular, the image quality problem may have problems with the current technology, but it will also have problems with the existing drone equipment. So, standard for drone calibration should also be established. Finally, the cadastral resurvey surveying procedure using drones was also presented.

The increasing use of drones in terrorist attacks highlights the need for effective strategies to prevent and respond to drone terrorism. This study uses machine learning approach to identify factors that predict the success of drone terrorism and suggests policy alternatives for preventing such acts. Drone terrorism is becoming increasingly accessible due to advancements in information and communication technology, and events such as North Korea’s drone infiltration and the Russia-Ukraine war demonstrate the potential threat of drone attacks on Important National Facilities, including nuclear power plants. Using the Global Terrorism Database (GTD), this study analyzed drone terrorism incidents that occurred worldwide from 2016 to 2020. The study employed the Random Forest algorithm, which can incorporate multiple factors and their interactions, making it particularly suitable for social science research. The study provides new insights by deriving predictors that were previously overlooked in empirical analyses of drone terrorism. The findings of this study can aid in the establishment of anti-terrorism policies aimed at addressing the growing threat of drone terrorism. This can include the organization and expansion of the crisis management governance terrorism response council, the creation of a working manual through the partial revision of laws concerning drone terrorism response, and the implementation of anti-drone equipment and systems. Ultimately, the insights gained from this study can provide development of effective strategies aimed at preventing and responding to drone attacks. The study highlights the importance of proactive measures to mitigate the risks posed by drone technology in the context of terrorism.

With the development of drone technology, drones are being used in various industries. In general, drones use lithium-based battery pack, which is sensitive to external impact and temperature characteristics. Therefore, in order to prevent this problem, a battery case for protecting the battery from the outside is used. Usually, carbon fiber is used as case material, carbon fiber is expensive and has disadvantages of being difficult to manufacture. In this study, a battery case was fabricated to minimize the influence of external impact and temperature by using expanded polypropylene material, and also the battery efficiency test was performed using fabricated case. After basic design for battery case was conducted, a system capable of maintaining temperature was constructed by attaching a surface heating element inside the case, and the effect of maintaining temperature according to the presence or absence of the case was confirmed. Using manufactured prototype case, flight tests were carried out to check the battery voltage level according to the presence or absence of the case and to analyze the effect of improving the battery efficiency for the flight time of the drone.

본 연구는 수직 벽체형 콘크리트 구조물의 정밀안전진단을 위한 외관조사시 고품질 정밀영상을 자동화된 방식으로 획득하여 균열손상을 탐지하고 시설물의 상태를 평가하기 위하여 개발된 등벽드론 탑재형 균열진단 시스템에 대한 것이다. 본 논문에서는 영상기반 균열진단 시스템을 이용한 정밀영상 획득기술, 자동화된 영상처리 알고리즘을 이용한 데이터 처리 기법을 제시하였으며, 실험적으로 도출된 지상표본거리를 기반으로 영상처리 자동화 알고리즘을 이용하여 생성된 균열모사 시험벽체의 평면전개 이미지 상 균열손상의 위치 정확도를 평가 분석하였다. 평가분석 결과, 가로축 길이 대비 최대 1.1%, 세로축 길이 대 비 최대 1.4%의 오차율을 보이는 것으로 나타났다. 제안된 영상 내 픽셀 좌표와 지상표본거리를 기반으로 균열손상의 위치를 추정하는 기법은 실측 좌표 대비 평균 1.0% 이하의 위치 오차를 가지는 것으로 평가되었다. 최종적으로 영상기반 진단과 긴급 보수와 같은 일반적인 시설물의 유지관리에 요구되는 위치 정확도를 확보하고 있는 것으로 분석되었다.

This research is to study the solution to the defects in maintenance and inspection that can be predicted/prevented in advance among human factors that account for more than 70% of the causes of aviation accidents. Traditionally, mechanics have performed visual inspections of aircraft exteriors. Due to this, there were factors that affect the human ability of mechanics in aircraft maintenance and inspection, safety problems when performing the upper part of the aircraft inspection, and the difficulty of precise inspection. To improve these problems, we conduct a study on an AI drone inspection system that has deep-learned samples on aircraft damage/defects. In this paper, we describe the aircraft maintenance inspection checklist, non-destructive inspection types, types of aircraft damage and defects, deep-learning highly reliable AI drone inspection systems, and the expected effects of this technology and future applications. Through this system research, it is expected that mechanics will efficiently inspect the aircraft through the optimization of aircraft maintenance system technology to prevent aviation accidents in advance and reduce time and economic costs.