[1]毕晓君,孙梓玮,刘进.高层火灾智能报警及逃生指导系统[J].智能系统学报,2022,17(4):814-823.[doi:10.11992/tis.202110018]
BI Xiaojun,SUN Ziwei,LIU Jin.Intelligent fire alarm and escape guidance systems for highrise buildings[J].CAAI Transactions on Intelligent Systems,2022,17(4):814-823.[doi:10.11992/tis.202110018]
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《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
17
期数:
2022年第4期
页码:
814-823
栏目:
学术论文—机器感知与模式识别
出版日期:
2022-07-05
- Title:
-
Intelligent fire alarm and escape guidance systems for highrise buildings
- 作者:
-
毕晓君1, 孙梓玮1, 刘进2
-
1. 中央民族大学 信息工程学院,北京 100081;
2. 哈尔滨工程大学 信息与通信工程学院,黑龙江 哈尔滨 150001
- Author(s):
-
BI Xiaojun1, SUN Ziwei1, LIU Jin2
-
1. School of Information Engineering, Minzu University of China, Beijing 100081, China;
2. Department of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China
-
- 关键词:
-
火灾报警系统; 无线保真; 火灾探测器; 现场可编程逻辑门阵列; 套接字; 行人检测; 中值滤波; 同态滤波
- Keywords:
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fire alarm systems; wireless fidelity; fire detectors; field programmable gate array; socket; pedestrian detection; median filtering; homomorphic filtering
- 分类号:
-
TP277
- DOI:
-
10.11992/tis.202110018
- 摘要:
-
现有高层火灾报警系统因报警滞后,缺乏火灾定位以及逃生引导,导致现场人员伤亡较大。为此,设计了具有精准定位、高效报警以及智能逃生引导功能的火灾警报系统。通过TXW8301-WiFi模块、火灾探测器和语音单片构成节点设备,布控在建筑内各区域,可自动检测火灾发生,并第一时间在各楼层播报火灾位置及具体的逃生指引路线,可以解决高层建筑距离远、隔断多造成因不知情、不清楚逃生路线而错失最佳逃生时机的问题。除自动报警引导功能外,本系统通过对通道监控视频进行去烟补光和去噪处理,并基于深度学习算法进行行人密度检测,可以根据逃生通道的拥堵情况进行多次逃生指导,最终所有信息将在系统总控界面显示,方便统一救援指挥,可最大限度地降低火灾中的人员伤亡。
- Abstract:
-
Due to delayed alarms, lack of fire positioning, and lack of escape guidance, existing highrise fire alarm systems caused large casualties on the scene. Thus, this paper designs a fire alarm system with precise positioning, high-efficiency alarm, and intelligent escape guidance functions. It can be deployed in various areas of the building using the TXW8301-WiFi module, fire detector, and voice monolithic to form a node device, which can automatically detect the occurrence of a fire and broadcast the fire location and specific escape guidance routes on each floor as soon as possible, which can solve the problem of highrise buildings. Due to unknown and unclear escape routes, the long distance between buildings and many partitions causes the problem of missing the best time to escape. In addition to the automatic alarm guidance function, the system uses the channel monitoring video to remove smoke, add light and denoise, and perform pedestrian density detection based on deep learning algorithms. It can conduct multiple escape guidance according to the congestion of the escape channel, and finally, all the information will be displayed on the system’s main control interface to facilitate unified rescue command and minimize fire casualties.
备注/Memo
收稿日期:2021-10-18。
作者简介:毕晓君, 教授,博士生导师,主要研究方向为智能信息处理技术、数字图像处理、机器学习。主持国家重点研发计划项目、国家社科基金重大项目等国家级、省部级项目 6 项。获高等学校科学技术进步一等奖 1 项、省部级科学技术奖 7 项。发表学术论 文170余篇;孙梓玮,硕士研究生,主要研究方向为目标检测、图像增强;刘进,硕士研究生,主要研究方向为深度学习算法在边缘设备上的优化部署
通讯作者:毕晓君. E-mail:bixiaojun@hrbeu.edu.cn
更新日期/Last Update:
1900-01-01