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감식 데이터 딥러닝을 활용한 드론 제어패턴 연구 : 재난현장 및 실종자 수색을 중심으로
A Study using Drone Control Patterns using Deep Learning of Investigation Data : Focusing on Disaster Scene and Search for Missing Persons

첫 페이지 보기
  • 발행기관
    한국화재감식학회 바로가기
  • 간행물
    한국화재감식학회 학회지 바로가기
  • 통권
    제11권 제4호 (2020.12)바로가기
  • 페이지
    pp.101-112
  • 저자
    박창우, 이창조
  • 언어
    한국어(KOR)
  • URL
    https://www.earticle.net/Article/A391320

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원문정보

초록

영어
Statistics of missing persons information system by the National Police Agency indicated a total of 42,390 missing reports of children, intellectually disabled and dementia patients in 2019. Also, according to the date statistics by the National Fire Agency, 40,000 to 50,000 fires broke out annually in Korea, resulting in massive loss of lives and property. For this reason, research on various algorithms on disaster sites and searching methods for missing persons continues, especially drone technology with automatic search and analysis functions are being developed by using artificial intelligence(AI). This study aims at utilizing a drone which is one of many unmanned equipment to collect the most accurate and the largest data in time by minimizing the site damage. To collect the data for searching missing persons and identifying disaster sites, aviation video and photography, 3D mapping, and special equipment can be mounted on drones to take 360-degree panoramic photographs and images. For data acquisition, drone control patterns were studied for searching for missing persons and identifying disaster sites by applying data elements extracted from the researcher's preceding research, so that Deep Learning pattern recognition algorithm can be applied to the latest AI technology. This pattern is the most critical element for unmanned mobile device control technology including AI drones for missing person research and disaster sites. The images for 2D and 3D modeling of videos ad photographs, which were taken by drones by applying Deep Learning elements to drone search patterns, were analyzed based on the production of modeling results and data with PIX4D software. In many cases, the cause of the serious loss of life at the disaster and missing search site is the golden time delay in the search and the Human Error during the inspection/diagnosis of the site. Therefore, there is a need of pattern development of the unmanned drones for the reconnaissance patrol by using Deep Learning elements, in order to compensate for the lack of professional manpower for diagnosis/inspection as well as search equipment. For this reason, we suggest the joint search patterns of aviation drones and floating/underwater drones for the follow-up studies.

목차

Abstract
1. 서론
2. 본론
2.1 실종자 수색에 필요한 딥러닝 요소의 항공드론 수색 패턴 적용
2.2 화재현장에서 필요한 딥러닝 요소의 항공드론 수색 패턴 적용
3. 결론
참고문헌

키워드

Distinguished data Using drone Deep learning Disaster scene Search Patterns for missing persons

저자

  • 박창우 [ Chang Woo Park | 우송대학교 드론아카데미 ]
  • 이창조 [ Chang Jo Lee | 우송대학교 ]

참고문헌

자료제공 : 네이버학술정보

간행물 정보

발행기관

  • 발행기관명
    한국화재감식학회 [Fire Investigation Socity of Korea]
  • 설립연도
    2009
  • 분야
    공학>공학일반
  • 소개
    화재의 과학적 감식, 원인규명 및 예방을 위한 학문과 기술의 발전을 도모하고, 산, 학, 연, 정의 상호 교류를 통한 화재예방과 조사 및 감식의 전문화와 함께 소방관련 정책방향 발전에 공한하며, 회원 및 화재 관련 분야의 국.내외 인사들과의 정보 교류를 위하여 설립되었다.

간행물

  • 간행물명
    한국화재감식학회 학회지 [Magazine of Fire Investigation Socity of Korea]
  • 간기
    계간
  • pISSN
    2092-531X
  • 수록기간
    2009~2026
  • 등재여부
    KCI 등재
  • 십진분류
    KDC 539 DDC 628

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