• Title/Summary/Keyword: Drone technology

Search Result 524, Processing Time 0.023 seconds

Topographic Variability during Typhoon Events in Udo Rhodoliths Beach, Jeju Island, South Korea (제주 우도 홍조단괴해빈의 태풍 시기 지형변화)

  • Yoon, Woo-Seok;Yoon, Seok-Hoon;Moon, Jae-Hong;Hong, Ji-Seok
    • Ocean and Polar Research
    • /
    • v.43 no.4
    • /
    • pp.307-320
    • /
    • 2021
  • Udo Rhodolith Beach is a small-scale, mixed sand-and-gravel beach embayed on the N-S trending rocky coast of Udo, Jeju Island, South Korea. This study analyzes the short-term topographic changes of the beach during the extreme storm conditions of four typhoons from 2016 to 2020: Chaba (2016), Soulik (2018), Lingling (2019), and Maysak (2020). The analysis uses the topographic data of terrestrial LiDAR scanning and drone photogrammetry, aided by weather and oceanographic datasets of wind, wave, current and tide. The analysis suggests two contrasting features of alongshore topographic change depending on the typhoon pathway, although the intensity and duration of the storm conditions differed in each case. During the Soulik and Lingling events, which moved northward following the western sea of the Jeju Island, the northern part of the beach accreted while the southern part eroded. In contrast, the Chaba and Maysak events passed over the eastern sea of Jeju Island. The central part of the beach was then significantly eroded while sediments accumulated mainly at the northern and southern ends of the beach. Based on the wave and current measurements in the nearshore zone and computer simulations of the wave field, it was inferred that the observed topographic change of the beach after the storm events is related to the directions of the wind-driven current and wave propagation in the nearshore zone. The dominant direction of water movement was southeastward and northeastward when the typhoon pathway lay to the east or west of Jeju Island, respectively. As these enhanced waves and currents approached obliquely to the N-S trending coastline, the beach sediments were reworked and transported southward or northward mainly by longshore currents, which likely acts as a major control mechanism regarding alongshore topographic change with respect to Udo Rhodolith Beach. In contrast to the topographic change, the subaerial volume of the beach overall increased after all storms except for Maysak. The volume increase was attributed to the enhanced transport of onshore sediment under the combined effect of storm-induced long periodic waves and a strong residual component of the near-bottom current. In the Maysak event, the raised sea level during the spring tide probably enhanced the backshore erosion by storm waves, eventually causing sediment loss to the inland area.

A Study on the Operation of Multi-Beam Antenna for Airborne Relay UAV considering the Characteristics of Aircraft (비행체의 특징을 고려한 공중중계 무인기 다중빔 안테나 운용 방안)

  • Park, Sangjun;Lee, Wonwoo;Kim, Yongchul;Kim, Junseob;Jo, Ohyun
    • Journal of Convergence for Information Technology
    • /
    • v.11 no.4
    • /
    • pp.26-34
    • /
    • 2021
  • In the era of the Fourth Industrial Revolution, the future battlefield will carry out multi-area operations with hyper-connected, high-speed and mobile systems. In order to prepare for changes in the future, the Korean military intends to develop various weapons systems and form a multi-layer tactical network to support On The Move communication. However, current tactical networks are limited in support of On The Move communications. In other words, the operation of multi-beam antennas is necessary to efficiently construct a multi-layer tactical network in future warfare. Therefore, in this paper, we look at the need for multi-beam antennas through the operational scenario of a multi-layer tactical network. In addition, based on development consideration factors, features of rotary-wing and fixed-wing aircraft, we present the location and operation of airborne relay drone installations of multi-beam antennas.

A study on the degree of aging recognition of firefighters and countermeasures(focus on firefighters in Jeollanam-do) (소방공무원의 고령화 인식정도와 대응방안에 관한 연구(전라남도 소방공무원을 중심으로))

  • Ha, Kang Hun;Kim, Jae Ho;Choi, Jae Wook
    • Journal of the Korea Academia-Industrial cooperation Society
    • /
    • v.22 no.3
    • /
    • pp.398-407
    • /
    • 2021
  • Firefighters (who are responsible for people's safety) have one of the jobs that are expected to have problems due to aging in the workforce. An increase in the average age of firefighters can lead to serious social problems. The aim of this study is to survey firefighters in Jeollanam-do about their awareness of aging in firefighters, and to propose a plan to prepare them for aging through investigation and analysis of work problems that may occur due to an aging workforce. The survey shows that the higher the age group, the higher the awareness of aging firefighters, and the higher the total work experience and internal/external work experience, the higher the awareness of aging. As a plan to solve various problems that may arise from aging in firefighters, regular operation of physical fitness promotion programs, field work, job rotation, and managerial measures (such as a change of position to an administrative department) are prepared, and drone or robot technology is used. These solutions include the introduction of applied high-tech technologies to firefighting activities, establishment of retirement management policies, and preparation of plans to revitalize the connection to private employment. In order to maximize the applicability of the field, government institutional plans and preparations are essential.

Calculation of the Normal Operation Rate of Monitoring Hardware in the Long Tunnels of High-Speed and Urban Railways (고속 철도와 도시철도 장대터널 계측기기의 정상 작동율 산정 연구)

  • Woo, Jong-Tae
    • Journal of the Society of Disaster Information
    • /
    • v.18 no.1
    • /
    • pp.80-90
    • /
    • 2022
  • Purpose: The objective of this study was to improve smart monitoring and monitoring management technology in long tunnels by investigating and analyzing the normal operation rates of monitoring hardware in the long tunnels of high-speed and urban railways. Method: This study evaluated, analyzed, and compared the normal operation rate of 6-8 types of monitoring hardware for each long tunnel, targeting three high-speed railway lines with a long tunnel (i.e., Suseo-Pyeongtaek Line, Gyeongbu Line, and Honam Line) and two urban railway groups with a long tunnel (i.e., Seoul Metro Lines 5, 6, and 7, and 9). Result: The rank of the normal operation rate of monitoring hardware was in the order of Suseo-Pyeongtaek High-Speed Railway (92.1%), Seoul Metro Lines 5, 6, and 7 (85.8%), Seoul Metro Line 9 (85.2%), Gyeongbu High-speed Railway (80.5%), and Honam High-speed Railway (46.7%). Conclusion: The mean normal operation rate of the monitoring hardware in the three high-speed railway long tunnels was 83.4%, and that of the two urban railway long tunnels was 85.5%, indicating that the deviation between them was small. The mean normal operation rate of the monitoring hardware in the long tunnels of the five high-speed and urban railway lines was 84.2%.

Trade Facilitation for the Products of the Industry 4.0: The case of Customs Classification of Drone

  • Yi, Ji-Soo;Moon, So-Young
    • Journal of Korea Trade
    • /
    • v.23 no.8
    • /
    • pp.110-131
    • /
    • 2019
  • Purpose - This paper investigates the implications for facilitating trade in the products of Industry 4.0. To identify the issues caused by the conflicts of policy objectives such as applying the tariff concession under the ITA and imposing the export control, by exploring the case of classification of drones. Design/methodology - We adopted a single case study method to gain a deeper understanding of the complex and multifaceted issues of Customs classification in the context of facilitating trade in the products of Industry 4.0. This study employs the case of drones to explore how these issues of Customs classification affect trade facilitation. We ensured the internal validity of the study by confirming the pattern of the results with the existing theories. Findings - Our main findings can be summarised as follows: the intrinsic nature of the products that converge several technologies causes issues in the classification. The inconsistency in product classification delays customs clearance by hindering the Customs risk-management system that pinpoints products subject to controls. To address the issues, therefore, we proposed fundamental reforms of Customs to empower themselves with management roles. Facilitating trade in the products of Industry 4.0 requires more enhanced Customs capability. Therefore, the reforms should include comprehensive capacity-building activities, such as changes in staff-trainings, promotion system, organisation and culture. Customs also need roles in robust designing of cooperative systems to compensate for the lacks of controls and to ensure concrete risk management for expedited Customs procedures. As well, by equipping the Single Window of Customs with crucial control functions of other ministries, Customs need to support the cooperation. The role of harmonising various preaudits of other ministries with its own is another essential role that ensures predictability of clearance procedure. Originality/value - There are scanty studies in the field of knowledge about what obstacles exist and what solution is available in the course of transforming to 'Industry 4.0'. In filling out the gap of knowledge, this paper is of academic significance in that it applies the research theory on trade facilitation for the specific cases of classification of the product of Industry 4.0 to verify its effectiveness and to extend the subject of the studies to the scope of Industry 4.0. It also has practical significance in that the results have provided implications for reforms of Customs procedures to facilitate trade in the products of Industry 4.0.

Fabrication of Three-Dimensional Scanning System for Inspection of Mineshaft Using Multichannel Lidar (다중채널 Lidar를 이용한 수직갱도 조사용 3차원 형상화 장비 구현)

  • Soolo, Kim;Jong-Sung, Choi;Ho-Goon, Yoon;Sang-Wook, Kim
    • Tunnel and Underground Space
    • /
    • v.32 no.6
    • /
    • pp.451-463
    • /
    • 2022
  • Whenever a mineshaft accidentally collapses, speedy risk assessment is both required and crucial. But onsite safety diagnosis by humans is reportedly difficult considering the additional risk of collapse of the unstable mineshaft. Generally, drones equipped with high-speed lidar sensors can be used for such inspection. However, the drone technology is restrictively applicable at very shallow depth, failing in mineshafts with depths of hundreds of meters because of the limit of wireless communication and turbulence inside the mineshaft. In previous study, a three-dimensional (3D) scanning system with a single channel lidar was fabricated and operated using towed cable in a mineshaft to a depth of 200 m. The rotation and pendulum movement errors of the measuring unit were compensated for by applying the data of inertial measuring unit and comparing the similarity between the scan data of the adjacent depths (Kim et al., 2020). However, the errors grew with scan depth. In this paper, a multi-channel lidar sensor to obtain a continuous cross-sectional image of the mineshaft from a winch system pulled from bottom upward. In this new approach, within overlapped region viewed by the multi-channel lidar, rotation error was compensated for by comparing the similarity between the scan data at the same depth. The fabricated system was applied to scan 0-165 m depth of the mineshaft with 180 m depth. The reconstructed image was depicted in a 3D graph for interpretation.

Development of Data Analysis and Interpretation Methods for a Hybrid-type Unmanned Aircraft Electromagnetic System (하이브리드형 무인 항공 전자탐사시스템 자료의 분석 및 해석기술 개발)

  • Kim, Young Su;Kang, Hyeonwoo;Bang, Minkyu;Seol, Soon Jee;Kim, Bona
    • Geophysics and Geophysical Exploration
    • /
    • v.25 no.1
    • /
    • pp.26-37
    • /
    • 2022
  • Recently, multiple methods using small aircraft for geophysical exploration have been suggested as a result of the development of information and communication technology. In this study, we introduce the hybrid unmanned aircraft electromagnetic system of the Korea Institute of Geosciences and Mineral resources, which is under development. Additionally, data processing and interpretation methods are suggested via the analysis of datasets obtained using the system under development to verify the system. Because the system uses a three-component receiver hanging from a drone, the effects of rotation on the obtained data are significant and were therefore corrected using a rotation matrix. During the survey, the heights of the source and the receiver and their offsets vary in real time and the measured data are contaminated with noise. The noise makes it difficult to interpret the data using the conventional method. Therefore, we developed a recurrent neural network (RNN) model to enable rapid predictions of the apparent resistivity using magnetic field data. Field data noise is included in the training datasets of the RNN model to improve its performance on noise-contaminated field data. Compared with the results of the electrical resistivity survey, the trained RNN model predicted similar apparent resistivities for the test field dataset.

A Study on Analysis of Construction Monitoring Cost and Improvement Measures of Railway Tunnel Construction in Seoul (서울시 철도터널 건설공사의 공사계측비 분석 및 개선방안 연구)

  • Jong-Tae Woo
    • Journal of the Society of Disaster Information
    • /
    • v.19 no.1
    • /
    • pp.18-30
    • /
    • 2023
  • Purpose: This study is to contribute to the development of monitoring technology through the increase of confidence in construction monitoring by deriving the analysis of construction monitoring cost and improvement measures of railway tunnel construction in Seoul. Method: It presents the status on design and contract of construction monitoring cost, status on application construction monitoring cost and its analysis, analysis on safety management cost and quality management cost, expansion of application of the price calculation standard for monitoring management services to improve this, and monitoring for direct order of ordering organization. Results: If the monitoring management service that was meanwhile ordered as included in the construction work is performed by the directly selected company of ordering organization through the preliminary screening for bidding qualification, then the improvement of monitoring quality and the accurate monitoring data can be secured. Conclusion: For the price calculation standard for monitoring management service, the application of actual cost addition method under the Engineering Promotion Act and the calculation standard of monitoring management cost for standard estimation for ground survey should be extended through the direct order of ordering organization, not the method to be included in the net construction cost where it is performed by a subcontractor via contractor.

The Application Methods of FarmMap Reading in Agricultural Land Using Deep Learning (딥러닝을 이용한 농경지 팜맵 판독 적용 방안)

  • Wee Seong Seung;Jung Nam Su;Lee Won Suk;Shin Yong Tae
    • KIPS Transactions on Software and Data Engineering
    • /
    • v.12 no.2
    • /
    • pp.77-82
    • /
    • 2023
  • The Ministry of Agriculture, Food and Rural Affairs established the FarmMap, an digital map of agricultural land. In this study, using deep learning, we suggest the application of farm map reading to farmland such as paddy fields, fields, ginseng, fruit trees, facilities, and uncultivated land. The farm map is used as spatial information for planting status and drone operation by digitizing agricultural land in the real world using aerial and satellite images. A reading manual has been prepared and updated every year by demarcating the boundaries of agricultural land and reading the attributes. Human reading of agricultural land differs depending on reading ability and experience, and reading errors are difficult to verify in reality because of budget limitations. The farmmap has location information and class information of the corresponding object in the image of 5 types of farmland properties, so the suitable AI technique was tested with ResNet50, an instance segmentation model. The results of attribute reading of agricultural land using deep learning and attribute reading by humans were compared. If technology is developed by focusing on attribute reading that shows different results in the future, it is expected that it will play a big role in reducing attribute errors and improving the accuracy of digital map of agricultural land.

Development of Deep Learning Based Ensemble Land Cover Segmentation Algorithm Using Drone Aerial Images (드론 항공영상을 이용한 딥러닝 기반 앙상블 토지 피복 분할 알고리즘 개발)

  • Hae-Gwang Park;Seung-Ki Baek;Seung Hyun Jeong
    • Korean Journal of Remote Sensing
    • /
    • v.40 no.1
    • /
    • pp.71-80
    • /
    • 2024
  • In this study, a proposed ensemble learning technique aims to enhance the semantic segmentation performance of images captured by Unmanned Aerial Vehicles (UAVs). With the increasing use of UAVs in fields such as urban planning, there has been active development of techniques utilizing deep learning segmentation methods for land cover segmentation. The study suggests a method that utilizes prominent segmentation models, namely U-Net, DeepLabV3, and Fully Convolutional Network (FCN), to improve segmentation prediction performance. The proposed approach integrates training loss, validation accuracy, and class score of the three segmentation models to enhance overall prediction performance. The method was applied and evaluated on a land cover segmentation problem involving seven classes: buildings,roads, parking lots, fields, trees, empty spaces, and areas with unspecified labels, using images captured by UAVs. The performance of the ensemble model was evaluated by mean Intersection over Union (mIoU), and the results of comparing the proposed ensemble model with the three existing segmentation methods showed that mIoU performance was improved. Consequently, the study confirms that the proposed technique can enhance the performance of semantic segmentation models.