ETRI-Knowledge Sharing Plaform



논문 검색
구분 SCI
연도 ~ 키워드


학술대회 Forest Fire Monitoring System based on Aerial Image
Cited 37 time in scopus Download 6 time Share share facebook twitter linkedin kakaostory
김성현, 이원재, 박영수, 이현우, 이용태
International Conference on Information and Communication Technologies for Disaster Management (ICT-DM) 2016, pp.1-6
16MH4800, 무인기 탑재 복합형 센서 기반의 국지적 재난 감시 및 상황 대응을 위한 스마트 아이 기술 개발, 이용태
Since natural disaster annually leads to casualties and property damages, developments for ICT-based disaster management techniques are fostering to minimize economic and social losses. For this reason, it is essential to develop a customized response technology for a natural disaster. In this paper, we introduce a smart-eye platform which is developed for disaster recognition and response. In addition, we propose a deep-learning based forest fire monitoring technique, which utilizes images acquired from an unmanned aerial vehicle with an optical sensor. Via training for image set of past forest fires, the proposed deep-learning based forest fire monitoring technique is designed to be able to make human-like judgement for a new input image automatically whether forest fire exists 01 not. Through simulation results, the algorithm architecture and detection accuracy of the proposed scheme is verified. By applying the proposed automatic disaster recognition technique to decision support system for disaster management, we expect to reduce losses caused by disasters and costs required for disaster monitoring and response.
KSP 제안 키워드
Aerial images, Decision Support System(DSS), Detection accuracy, Disaster management, Disaster monitoring, Forest fire monitoring, Human-like, Management techniques, Monitoring and response, Monitoring system, Monitoring techniques