• Korean Journal of Remote Sensing
• /
• v.39 no.5_2
• /
• pp.837-847
• /
• 2023

In this study, we explored a method for assessing the extent of damage caused by chemical substances at an accident site through the use of a vegetation index. Data collection involved the deployment of two different drone types, and the damaged area was determined using photogrammetry technology from the 3D point cloud data. To create a vegetation index image, we utilized spectral band data from a multi-spectral sensor to generate an orthoimage. Subsequently, we conducted statistical analyses of the accident site with respect to the damaged area using a predefined threshold value. The Kappa values for the vegetation index, based on the near-infrared band and the green band, were found to be 0.79 and 0.76, respectively. These results suggest that the vegetation index-based approach for analyzing damage areas can be effectively applied in investigations of chemical accidents.

• The Korean Journal of Air & Space Law and Policy
• /
• v.34 no.1
• /
• pp.235-268
• /
• 2019

Under the Aviation Safety Act of Korea, any person who intends to operate a drone is required to follow the operational conditions listed below, unless approved by the Minister of Land, Infrastructure, Transport and Tourism; (i) Operation of drones in the daytime, (ii) Operation of drones within Visual Line of Sight, (iii) Maintenance of a certain operating distance between drones and persons or properties on the ground/ water surface, (iv) Do not operate drones over event sites where many people gather, (v) Do not transport hazardous materials such as explosives by drone, (vi) Do not drop any objects from drones. Requirements stated in "Airspace in which Flights are Prohibited" and "Operational Limitations" are not applied to flights for search and rescue operations by public organizations in case of accidents and disasters. This paper analyzes legal issues as to definition and regulations of drones in Korean Aviation Safety Act. This paper, also, offers some implications and suggestions for regulations of drones under Korean Aviation Safety Act by comparing the regulations of drones in Japanese Civil Aeronautics Act.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.18 no.1
• /
• pp.195-204
• /
• 2023

The drone's battery system uses lithium-ion or lithium-polymer batteries, and it is known that the cause of fire during the disposal process after using the drone is combustible gas from the battery being discarded. Most of the batteries in the disposal process generated oxygen, but a small amount of flammable gas was also generated, and a large amount of chlorine ions and sulfates were also detected in the equipment used for treatment. If a system that detects this early is configured, it will be possible to reduce the risk of accidents caused by discarded batteries.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2023.07a
• /
• pp.451-452
• /
• 2023

고속도로에 낙하물이 있으면 사고 방지를 위해 바로 치워야 하지만 순찰차가 발견하거나 신고가 들어오기 전까진 낙하물을 바로 발견하기 힘들며, 대다수의 사람들은 신고하지 않고 지나치는 경우가 있기에 이러한 문제점들을 개선하기 위해 드론과 YOLO를 이용하여 도로의 낙하물을 인식하고 낙하물에 대한 정보를 보내 줄 수 있는 시스템을 개발하였다. 실시간 객체 인식 알고리즘인 YOLOv5를 데스크톱 PC에 적용하여 구현하였고, F450 프레임에 픽스호크와 모듈, 카메라를 장착하여 실시간으로 도로를 촬영할 수 있는 드론을 직접 제작하였다. 개발한 시스템은 낙하물에 대한 인식 결과와 정보를 제공하며 지상관제 시스템과 웹을 통해 확인할 수 있다. 적은 인력으로 더 빠르게 낙하물을 발견할 수 있으므로 빠른 상황 조치를 기대할 수 있다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2017.11a
• /
• pp.961-964
• /
• 2017

드론의 대중화에 따른 사고위험의 증가로 안전한 조종 방법에 대한 연구의 필요성이 대두되었다. 따라서 조종자의 조종능력에 구애받지 않는 자율비행제어기술이 필요하게 되었고, 이를 보다 안정적으로 구현하기 위하여 자율주행 소프트웨어 플랫폼으로 주목받고 있는 Robot Operating System(ROS)를 사용하였다. ROS를 기반으로 Laser Range Finder(LRF)와 Particle Filter를 사용하여 자율적으로 객체추적이 가능하며 지능적으로 장애물을 회피하여 비행 할 수 있는 안정적인 자율비행제어시스템을 구현하고자 한다.

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

• The Journal of the Convergence on Culture Technology
• /
• v.9 no.4
• /
• pp.277-281
• /
• 2023

Recent aggressive threats by North Korea using small drones have heavily impacted on ROK(Republic of Korea) society and it seems to be agreed that counter-drone systems are required to protect our properties. ROK government has been investigating current counter-drone systems for national important facilities. However, there is no consensus standard to evaluate the systems. This paper is to propose a counter-drone system evaluation framework which is the outcome through RMA(Revolution in Military Affairs) thinking process. The RMA thinking process is currently well-implemented in ROK army to develop future military strategy. The proposed framework has 4 categories - threat analysis of North Korea small drones, convergence of detection, tracking and neutralizing systems, integrated operations and available experts and organization - which have corresponding criteria.

• The Journal of the Convergence on Culture Technology
• /
• v.9 no.6
• /
• pp.789-793
• /
• 2023

Evalution of counter drone systems is conducted in order to designate plausible countermeasues against possible drone threats, assess the level of safety of national major facilities and derive complementary measures for detected weakness. Recently drone threats by North Korea have heavily impacted ROK(Republic of Korea) people and it has been stronly stressed to build efficient counter drone system for make the society protected and secured against drone threats. The researchers has conducted field investigations for some of national major facilites. There is, however, no standardized evaluation checklist, so we have proposed an evaluation checklist for counter drone systems though thinking process of RMA(Revolution in Military Affairs). This paper is to introduce the evaluation checklist for properly diagnosing each counter drone system.

• The Journal of the Korea Contents Association
• /
• v.19 no.11
• /
• pp.111-121
• /
• 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.

• Korean Journal of Remote Sensing
• /
• v.39 no.6_1
• /
• pp.1451-1466
• /
• 2023

In the context of maritime emergencies, the utilization of drones has rapidly increased, with a particular focus on their application in search and rescue operations. Deep learning models utilizing drone images for the rapid detection of distressed vessels and other maritime drift objects are gaining attention. However, effective training of such models necessitates a substantial amount of diverse training data that considers various weather conditions and vessel states. The lack of such data can lead to a degradation in the performance of trained models. This study aims to enhance the performance of deep learning models for distress ship detection by developing a maritime environment simulator to augment the dataset. The simulator allows for the configuration of various weather conditions, vessel states such as sinking or capsizing, and specifications and characteristics of drones and sensors. Training the deep learning model with the dataset generated through simulation resulted in improved detection performance, including accuracy and recall, when compared to models trained solely on actual drone image datasets. In particular, the accuracy of distress ship detection in adverse weather conditions, such as rain or fog, increased by approximately 2-5%, with a significant reduction in the rate of undetected instances. These results demonstrate the practical and effective contribution of the developed simulator in simulating diverse scenarios for model training. Furthermore, the distress ship detection deep learning model based on this approach is expected to be efficiently applied in maritime search and rescue operations.