• Journal of Korea Multimedia Society
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• v.22 no.10
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• pp.1178-1186
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• 2019

In recent years, interest in drones has grown, and many countries are developing them into a strategic industry of the future. Drones are not only used in industries such as logistics and agriculture but also in various public sectors such as life rescue, disaster investigation, traffic control, and firefighting. One of the most important tasks of a drone is to accurately identify targets in these applications. Target recognition may vary depending on the search environment of the drone. Therefore, this study tests and analyzes the drone's target recognition performance according to changes in the search environment such as the search altitude and the search angle. In addition, we propose a new algorithm that improves upon the disadvantages of the Haar cascade method, which is the existing algorithm that recognizes the target by analyzing a captured image.

• Journal of Internet Computing and Services
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• v.23 no.4
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• pp.57-64
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• 2022

If the inside of a building collapses due to a disaster such as fire, collapse, or natural disaster, the physical security inside the building is likely to become ineffective. Here, physical security is needed to minimize the human casualties and physical damages in the collapsed building. Therefore, this paper proposes an algorithm to minimize the damage in a disaster situation by fusing existing research that detects obstacles and collapsed areas in the building and a deep learning-based object detection algorithm that minimizes human casualties. The existing research uses a single camera to determine whether the corridor environment in which the robot is currently located has collapsed and detects obstacles that interfere with the search and rescue operation. Here, objects inside the collapsed building have irregular shapes due to the debris or collapse of the building, and they are classified and detected as obstacles. We also propose a method to detect rescue requesters-the most important resource in the disaster situation-and minimize human casualties. To this end, we collected open-source disaster images and image data of disaster situations and calculated the accuracy of detecting rescue requesters in disaster situations through various deep learning-based object detection algorithms. In this study, as a result of analyzing the algorithms that detect rescue requesters in disaster situations, we have found that the YOLOv4 algorithm has an accuracy of 0.94, proving that it is most suitable for use in actual disaster situations. This paper will be helpful for performing efficient search and rescue in disaster situations and achieving a high level of physical security, even in collapsed buildings.

• Journal of the Korean Society of Marine Environment & Safety
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• v.6 no.1
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• pp.111-120
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• 2000

In this study the drift prediction models currently used in search and rescue(SAR) operations are introduced and the basic differences among them are analyzed by comparing the target classification, the treatment of environmental conditions, leeway equations and the determination of search area. In addition the new methods under development including AP98 of U.S. Coast Guard are compared and studied to improve the efficiency of SAR operation.

• Proceedings of KOSOMES biannual meeting
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• 2017.11a
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• pp.80-80
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• 2017

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2015.10a
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• pp.87-90
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• 2015

Equipments that can transmit maritime distress signals in accordance to Global Maritime Distress Safety System are the followings: A1 water(Very High Frequency, SART), A2 water(MF/HF Radio Equipment), A3 water(INMARSAT), A4 water(Emergency Position Indicating Radio Beacon). Institutions with the capacity to receive distress signals are Korea Coast Guard affiliated radio stations, patrol ships, Rescue Coordination centers, Vessel Traffic centers, Complex problems regarding repetitive distress alarms, inaccurate statistics, multiple control towers are existent. Consequently, effective measurement to resolve dispersed operating maritime distress signal system are in time of need. Moreover, current KCG Headquarter is considering to integrate five distress radio stations dispersed across nation into a single international safety communication center. The integration of radio stations are efficient in terms of information coordination between nations, however, it cannot support efficient response to real-time maritime incident. Therefore, in this study, a new system that can rapidly response to real-time maritime incident will be proposed.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1048-1053
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• 2005

This paper presents design and integration of the ROBHAZ-DT3, which is a newly developed mobile robot system with chained double-track mechanisms. A passive adaptation mechanism equipped between the front and rear body enables the ROBHAZ-DT3 to have good adaptability to uneven terrains including stairs. The passive adaptation mechanism reduces energy consumption when moving on uneven terrain as well as its simplicity in design and remote control, since no actuator is necessary for adaptation. Based on this novel mobile platform, a rescue version of the ROBHAZ-DT3 with appropriate sensors and a semi-autonomous mapping and localization algorithm is developed to participate in the RoboCup2004 US-Open: Urban Search and Rescue Competition. From the various experiments in the realistic rescue arena, we can verify that the ROBHAZ-DT3 is reliable in traveling rugged terrain and the proposed mapping and localization algorithm are effective in the unstructured environment with uneven ground. The another application is an military robot for an EOD(Explosive Ordnance Disposal) and reconnaissance mission. The military version of the ROBHAZ-DT3 with a water disrupter, a thermal scope and a long distance wireless communication device is developed and sent to the area of military tactics in Iraq. Consequently, the feasibility of the military version of ROBHAZ-DT3 is verified.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2002.11a
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• pp.1-6
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• 2002

To provide an easy operation of drift prediction model in SAR(search and rescue) mission a GUI program running on Window environment has developed. Users can make choice of input data on the screen by just clicking the mouse and the prediction results of datum points and trajectories of vessels are drawn on the map. The program contains both Leeway Equation model and mathematical model. The FORTRAN language was used in programming and Lehay Winteracter 4.0 software was utilized for graphic presentation. The result of May, 2001 Busan field experiment was plotted with that of model prediction for demonstration purpose.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.5 no.1
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• pp.11-18
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• 1993

A key element of a successful search and rescue is the correct prediction of the target location. In this paper, new computer models for drift prediction are suggested from the analysis of several methods currently used in other countries. Depending on the availability of the environmental data, users may select a model between the modified versions of U.S. Coast Guard CASP and FLENUMWEACEN SAR. Targets include boats, life rafts and person in water. Life rafts and boats are further classifed. New models are tested and compared with the limited number of field experimental results.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.582-585
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• 2011

During disaster response, prioritization of limited resources is one of the most important bust challenging tasks. At the same time, it is imperative to timely provide the rescuers with the adequate equipment to facilitate lifesaving operations. However, supply of high demand equipment was insufficient during the initial phase of disaster response, challenging lifesaving operations in the case of the 9-11 terrorist attacks. In respond to the Haiti Earthquake, spatial information of the geographic area was not sufficient to support the search and rescue operations in the early phase of disaster response. However, with the help of civilians, information such as road names, infrastructure damage, and victim locations were updated into the spatial data repository. At the same time, resource outside of the disaster affected zone converges into the area to assist the response efforts, which is the effect of convergence that often made resource coordination challenging in large scale disasters. To efficiently collect information and utilize the converging resources, this paper proposes a flexible data repository for information update for equipment utilization in large scale disaster response scenarios.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.10a
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• pp.143-144
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• 2009