AI-enhanced fire detection and suppression system for autonomous ships☆

被引:1
|
作者
Lee, Hyuk [1 ]
Chung, Jung Hoon [1 ]
Chung, Hyun [2 ]
Kim, Jong-Hwan [3 ]
Yoo, Yongho [4 ]
Lim, Gil Hyuk [5 ]
Ruy, Won-Sun [2 ]
机构
[1] Korea Inst Machinery & Mat, Dept Syst Dynam, Daejeon, South Korea
[2] Chungnam Natl Univ, Dept Autonomous Vehicle Syst Engn, Daejeon, South Korea
[3] Korea Mil Acad, Dept Mech & Syst Engn, Seoul, South Korea
[4] Korea Inst Civil Engn & Bldg Technol, Fire Res Inst, Goyang, Gyeonggi Do, South Korea
[5] Super Century Co Ltd Inst, Daejeon, South Korea
关键词
Autonomous fire detection and suppression; system; Artificial intelligence; Sensor fusion; Stereo vision; Ship motion;
D O I
10.1016/j.ijnaoe.2024.100628
中图分类号
U6 [水路运输]; P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
The rapid propagation of fire after a flashover can result in significant economic losses and human casualties. Meanwhile, the shipping industry faces crew shortages, making unmanned fire detection crucial for reducing manpower while ensuring seamless operations. Although autonomous fire detection and suppression systems (AFDSS) have been applied in tunnels and building infrastructure, no specialized AFDSS exists for unmanned autonomous ships, where minimizing false alarms and ensuring precise fire suppression under irregular wave conditions are critical. In this paper, we introduce an innovative AFDSS that integrates RGB, infrared (IR), and ultraviolet (UV) sensors to reduce false alarms and employ a reinforcement learning algorithm to optimize water spray under sea conditions. We present the design, system integration, and fire-extinguishing experiments, demonstrating the effectiveness of the system in enhancing the fire safety of autonomous ships under simulated sea-state conditions.
引用
收藏
页数:17
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