• Title/Summary/Keyword: Drone Road

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Development of underwater drone for underwater envorment image acquisition and road view interface enviroment (수중 환경 정보 채집용 수중드론 개발 및 수중 로드뷰 인터페이스 환경 구축 개발)

  • Je-Hui Jeon;Hang-Duck Jo;Tea-Min Kim;Ji-Seok Yu;Yeong-Ki Gwon;Jian Kim
    • Proceedings of the Korea Information Processing Society Conference
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    • 2023.11a
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    • pp.959-960
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    • 2023
  • 본 연구에서는 수중 환경 정보 수집과 수집된 환경 정보를 쉬운 인터페이스 환경 구축하고자 부력제어 방식의 수중 드론을 제작하고 수중 지형 지물의 로드뷰 제작 기법을 개발 수행한다.

Applicability Review of Street Dimensional Data Survey Using Point Clouds Generated from Drone Photogrammetry (드론 항공사진측량 기반 포인트 클라우드 데이터를 활용한 가로환경 조사 가능성 연구)

  • Oh, Sunghoon;Kim, Myung Jo
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.39 no.6
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    • pp.401-408
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    • 2021
  • With the proposal of amendments to the Pedestrian Safety Act in 2021, when the amendment bill is passed in the near future, a general dimensional investigation of the sidewalks' physical condition, which is the basis of pedestrian safety, is expected to be legislated and made mandatory. Therefore, this study presented a affordable methodology for street environment survey using entry-level drones and examined the feasibility of conducting a complete survey of pedestrian paths by local governments nationwide. To this end, various street facilities in the experimental site were measured to compare and analyze the accuracy of the point cloud data. As a result of the analysis, it was found that the measurement error range satisfies the public surveying guidelines. If the methodology presented in this study is applied, it is expected that individual local governments will be able to make a significant contribution to monitoring the physical conditions of streets to improve the pedestrian environment in the near future.

A Study on the Quality Control Plan for Bridge Pavement using drones (드론을 활용한 교면포장 품질관리 방안에 관한 연구)

  • Song, Mihwa;Gil, Heungbae
    • Journal of the Korea Convergence Society
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    • v.13 no.5
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    • pp.1-8
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    • 2022
  • In Korea, drones, which are at the core of the 4th industrial revolution, are used to promote Korean New Deal policies to digitalize the SOC. Overseas, the use of convergence sensors, such as thermal imaging cameras, on drones is increasing in various industrial fields. In this research, to improve pavement quality in highway bridge pavement construction, a thermal imaging camera was mounted on a drone to measure and verify the temperature of the pavement work section. Using a laser thermometer allows the partial measurement of pavement temperature. It was confirmed that the proposed method allows not only real-time temperature monitoring of the whole pavement work section but also uniformity verification by checking temperature distribution. The proposed method has the potential to control highway pavement quality and enable quick decision-making on traffic opening times by reducing the possibility of misjudging road opening times(pavement surface temperature ≦ 40℃).

Implementation of YOLO based Missing Person Search Al Application System (YOLO 기반 실종자 수색 AI 응용 시스템 구현)

  • Ha Yeon Km;Jong Hoon Kim;Se Hoon Jung;Chun Bo Sim
    • Smart Media Journal
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    • v.12 no.9
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    • pp.159-170
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    • 2023
  • It takes a lot of time and manpower to search for the missing. As part of the solution, a missing person search AI system was implemented using a YOLO-based model. In order to train object detection models, the model was learned by collecting recognition images (road fixation) of drone mobile objects from AI-Hub. Additional mountainous terrain datasets were also collected to evaluate performance in training datasets and other environments. In order to optimize the missing person search AI system, performance evaluation based on model size and hyperparameters and additional performance evaluation for concerns about overfitting were conducted. As a result of performance evaluation, it was confirmed that the YOLOv5-L model showed excellent performance, and the performance of the model was further improved by applying data augmentation techniques. Since then, the web service has been applied with the YOLOv5-L model that applies data augmentation techniques to increase the efficiency of searching for missing people.

Service Design for Using the Drones in the Early Stages Fires of Dense Residential Areas (주택가 밀집지역 화재발생 초기 드론 활용 서비스디자인 연구)

  • Youn, Gyo-Hee
    • The Journal of the Korea Contents Association
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    • v.19 no.11
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    • pp.111-121
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    • 2019
  • Recently, through the services that use drones at fire sites to deliver on-site and road conditions into the situation room and life-saving activities or the deliveries of first aid outfits at the accident scenes that are inaccessible to humans, there are more and more cases of dealing with emergency situations. Therefore, by studying the service design using drones in the initial stage of response to fires in dense residential areas, this study was intended to reify the service design area of the response stage, including the dispatch of fire sites and the fire suppression. To do this, through literature researches, research directions were explored by examining the concept and process review of service design, and by analyzing the application cases using service design. In order examine the validity of this study, a one-on-one interview was conducted to identify the use and problems of drones among incumbent firefighters, and identified the applicability of drones to fire sites by targeting drone experts. Field research was conducted to identify the location and distance of road conditions, site conditions, and 119 safety centers, by making Yongsan-gu, the most vulnerable area to fire in Seoul, as a research sample. And, among the methodologies of service design, Persona and Customer Journey Map were prepared and Insight was derived, by using virtual scenarios for the experience values and behavior analyses of the interested parties. Through these processes, this researcher intended to present the fire-response service design and help establish the direction of service design in the initial stages of fire in Korea.

Accuracy Analysis of Low-cost UAV Photogrammetry for Corridor Mapping (선형 대상지에 대한 저가의 무인항공기 사진측량 정확도 평가)

  • Oh, Jae Hong;Jang, Yeong Jae;Lee, Chang No
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.36 no.6
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    • pp.565-572
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    • 2018
  • Recently, UAVs (Unmanned Aerial Vehicles) or drones have gained popularity for the engineering surveying and mapping because they enable the rapid data acquisition and processing as well as their operation cost is low. The applicable fields become much wider including the topographic monitoring, agriculture, and forestry. It is reported that the high geospatial accuracy is achievable with the drone photogrammetry for many applications. However most studies reported the best achievable mapping results using well-distributed ground control points though some studies investigated the impact of control points on the accuracy. In this study, we focused on the drone mapping of corridors such as roads and pipelines. The distribution and the number of control points along the corridor were diversified for the accuracy assessment. In addition, the effects of the camera self-calibration and the number of the image strips were also studied. The experimental results showed that the biased distribution of ground control points has more negative impact on the accuracy compared to the density of points. The prior camera calibration was favored than the on-the-fly self-calibration that may produce poor positional accuracy for the case of less or biased control points. In addition, increasing the number of strips along the corridor was not helpful to increase the positional accuracy.

Development of Deep Learning Model for Detecting Road Cracks Based on Drone Image Data (드론 촬영 이미지 데이터를 기반으로 한 도로 균열 탐지 딥러닝 모델 개발)

  • Young-Ju Kwon;Sung-ho Mun
    • Land and Housing Review
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    • v.14 no.2
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    • pp.125-135
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    • 2023
  • Drones are used in various fields, including land survey, transportation, forestry/agriculture, marine, environment, disaster prevention, water resources, cultural assets, and construction, as their industrial importance and market size have increased. In this study, image data for deep learning was collected using a mavic3 drone capturing images at a shooting altitude was 20 m with ×7 magnification. Swin Transformer and UperNet were employed as the backbone and architecture of the deep learning model. About 800 sheets of labeled data were augmented to increase the amount of data. The learning process encompassed three rounds. The Cross-Entropy loss function was used in the first and second learning; the Tversky loss function was used in the third learning. In the future, when the crack detection model is advanced through convergence with the Internet of Things (IoT) through additional research, it will be possible to detect patching or potholes. In addition, it is expected that real-time detection tasks of drones can quickly secure the detection of pavement maintenance sections.

A Study on the Methodology for Analyzing the Effectiveness of Traffic Safety Facilities Using Drone Images (드론 영상기반 교통안전시설 효과분석 방법론 연구)

  • Yong Woo Park;Yang Jung Kim;Shin Hyoung Park
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.22 no.5
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    • pp.74-91
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    • 2023
  • Several that analyzed the effectiveness of traffic safety facilities a method of comparing changes in the number of accidents, accident severity, speed through traffic accident data before and after installation or speed data collected from vehicle detection systems (VDS). , when traffic accident data is used, it takes a long time to collect because must be collected for at least one year before and after installation. , the road environment may change during this period, such as the addition of other traffic safety facilities in addition to the facilities to be analyzed. , the location of the VDSs for speed data is often different from the location where analysis is required, and there is a problem in that the investigators are exposed to the risk of traffic accident during on-site investigation. Therefore, this study a case study by establishing a methodology to determine effectiveness video images with a drone, extracting data using a program, and comparing vehicle driving speeds before and after speed reduction facilities. Vehicle speed surveys using drones are much safer than observational surveys conducted on highways and have the advantage of tracking speed changes along the vehicle, it is expected that they will be used for various traffic surveys in the future.

Study on 3D Object (Building) Update and Construction Method for Digital Twin Implementation (디지털 트윈 구현을 위한 3차원 객체(건물) 갱신 및 구축 방안 연구)

  • Kwak, Byung-Yong;Kang, Byoung-Ju
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.44 no.4
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    • pp.186-192
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    • 2021
  • Recently, the demand for more precise and demand-oriented customized spatial information is increasing due to the 4th industrial revolution. In particular, the use of 3D spatial information and digital twins which based on spatial information, and research for solving social problems in cities by using such information are continuously conducted. Globally, non-face-to-face services are increasing due to COVID-19, and the national policy direction is also rapidly progressing digital transformation, digitization and virtualization of the Korean version of the New Deal, which means that 3D spatial information has become an important factor to support it. In this study, physical objects for cities defined by world organizations such as ISO, OGC, and ITU were selected and the target of the 3D object model was limited to buildings. Based on CityGML2.0, the data collected using a drone suitable for building a 3D model of a small area is selected to be updated through road name address and building ledger, which are administrative information related to this, and LoD2.5 data is constructed and urban space. It was intended to suggest an object update method for a 3D building among data.

3-dimensional Modeling and Mining Analysis for Open-pit Limestone Mine Stope Using a Rotary-wing Unmanned Aerial Vehicle (회전익 무인항공기를 이용한 노천석회석광산 채굴장 3차원 모델링 및 채굴량 분석)

  • Kang, Seong-Seung;Lee, Geon-Ju;Noh, Jeongdu;Jang, Hyeongdoo;Kim, Sun-Myung;Ko, Chin-Surk
    • The Journal of Engineering Geology
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    • v.28 no.4
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    • pp.701-714
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    • 2018
  • The purpose of this study is to show the possibility of 3-dimensional modeling of open-pit limestone mine by using a rotary-wing unmanned aerial vehicle, a drone, and to estimate the amount of mining before and after mining of limestone by explosive blasting. Analysis of the image duplication of the mine has shown that it is possible to achieve high image quality. Analysis of each axis error at the shooting position after analyzing the distortions through camera calibration was shown the allowable range. As a result of estimating the amount of mining before and after explosive blasting, it was possible to estimate the amount of mining of a wide range quickly and accurately in a relatively short time. In conclusion, it is considered that the drone of a rotary-wing unmanned aerial vehicle can be usefully used for the monitoring of open-pit limestone mines and the estimation of the amount of mining. Furthermore, it is expected that this method will be utilized for periodic monitoring of construction sites and road slopes as well as open-pit mines in the future.