火灾探测
探测器
计算机科学
人工智能
警报
实时计算
目标检测
假警报
计算机视觉
单发
恒虚警率
延迟(音频)
模式识别(心理学)
工程类
电信
建筑工程
物理
光学
航空航天工程
作者
Anh Quang Nguyen,Hong-Quan Nguyen,Van-Huy Tran,Huy Xuan Pham,Jesús Pestana
出处
期刊:International Conference on Communications
日期:2021-01-13
卷期号:: 338-343
被引量:37
标识
DOI:10.1109/icce48956.2021.9352080
摘要
Early fire detection and alarm are significantly important to reduce the losses caused by fire. Conventional methods in fire detection using smoke and heat detectors have disadvantages in accuracy, latency as well as the detection area. In this paper, we propose and implement a real-time fire detection solution for large area surveillance using the unmanned aerial vehicle with an integrated visual detection and alarm system. The system includes a low-cost camera, a light weight companion computer, a flight controller as well as localization and telemetry modules. To achieve real-time detection, Single Shot MultiBox Detector (SSD) algorithm is implemented as the heart of the system. We used MobileNets base model, which more efficient for mobile and embedded vision applications, instead of conventional VGG-16/ResNet model to achieve the mean average precision of 92.7% with the detection speed of 26 FPS.
科研通智能强力驱动
Strongly Powered by AbleSci AI