드론을 활용한 감식 데이터의 딥러닝에 관한 연구 : 재난현장 및 실종자 수색을 중심으로


A Study on Deep Learning of Distinguished Data Using Drones : Focusing on Disaster Scene and Search for Missing Persons

차정훈, 유재석, 박창우

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In the National Police Agency statistics According to In 2017 alone, children, the disabled and the elderly with dementia are reported missing. There are an average of 100 missing cases per day. In addition, according to data compiled by the National Defense Agency, there are 40,000 to 50,000 fires annually in Korea, Massive loss of life and property will result. Therefore, research on various algorithms for these disaster sites and search methods for missing persons continues, and drone technologies with automated search and analysis features are being developed, particularly using artificial intelligence. As a method of collecting data for searching for missing persons and identifying disaster sites, data such as 360 degree panoramic photos and images can be obtained by attaching aerial video and photography, 3D mapping, and special equipment to drones. Data acquisition aims to extract data analysis elements so that deep learning pattern recognition algorithms can be applied to the latest technology of artificial intelligence. Deep Learning's extraction of elements to search for various missing persons and detect disaster sites is the most important element in unmanned mobile device control technology including AI (Artificial Intelligence) drones. A number of causes of human casualties at the disaster site and the search for missing persons are due to the delay in searching for missing persons and the lack of human error during the inspection and diagnosis of the disaster site.


1. 서론
2. 본론
2.1 실종자 수색에 필요한 딥러닝 요소
2.2 화재현장에서 필요한 딥러닝 요소
2.3 드론을 활용해 획득한 데이터의 변환
3. 결론


  • 차정훈 Cha Jeoung Hun. 영동군청
  • 유재석 Yu Jae Suk. 충북소방본부
  • 박창우 Park Chang Woo. 우송대학교 드론아카데미


자료제공 : 네이버학술정보

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