AI-enhanced fire detection and suppression system for autonomous ships
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 a...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-01-01
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| Series: | International Journal of Naval Architecture and Ocean Engineering |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2092678224000475 |
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| author | Hyuk Lee Jung Hoon Chung Hyun Chung Jong-Hwan Kim Yongho Yoo Gil Hyuk Lim Won-Sun Ruy |
| author_facet | Hyuk Lee Jung Hoon Chung Hyun Chung Jong-Hwan Kim Yongho Yoo Gil Hyuk Lim Won-Sun Ruy |
| author_sort | Hyuk Lee |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-e864e9b885004e98a78a6929d3553303 |
| institution | OA Journals |
| issn | 2092-6782 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Naval Architecture and Ocean Engineering |
| spelling | doaj-art-e864e9b885004e98a78a6929d35533032025-08-20T02:35:18ZengElsevierInternational Journal of Naval Architecture and Ocean Engineering2092-67822024-01-011610062810.1016/j.ijnaoe.2024.100628AI-enhanced fire detection and suppression system for autonomous shipsHyuk Lee0Jung Hoon Chung1Hyun Chung2Jong-Hwan Kim3Yongho Yoo4Gil Hyuk Lim5Won-Sun Ruy6Department of System Dynamics, Korea Institute of Machinery and Material, Daejeon, Republic of KoreaDepartment of System Dynamics, Korea Institute of Machinery and Material, Daejeon, Republic of KoreaDepartment of Autonomous Vehicle System Engineering, Chungnam National University, Daejeon, Republic of KoreaDepartment of Mechanical & Systems Engineering, Korea Military Academy, Seoul, Republic of KoreaFire Research Institute, Korea Institute of Civil Engineering and Building Technology, Gyeonggi-do, Republic of KoreaSuper Century Co., Ltd Institute, Daejeon, Republic of KoreaDepartment of Autonomous Vehicle System Engineering, Chungnam National University, Daejeon, Republic of Korea; Corresponding author.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.http://www.sciencedirect.com/science/article/pii/S2092678224000475Autonomous fire detection and suppression systemArtificial intelligenceSensor fusionStereo visionShip motion |
| spellingShingle | Hyuk Lee Jung Hoon Chung Hyun Chung Jong-Hwan Kim Yongho Yoo Gil Hyuk Lim Won-Sun Ruy AI-enhanced fire detection and suppression system for autonomous ships International Journal of Naval Architecture and Ocean Engineering Autonomous fire detection and suppression system Artificial intelligence Sensor fusion Stereo vision Ship motion |
| title | AI-enhanced fire detection and suppression system for autonomous ships |
| title_full | AI-enhanced fire detection and suppression system for autonomous ships |
| title_fullStr | AI-enhanced fire detection and suppression system for autonomous ships |
| title_full_unstemmed | AI-enhanced fire detection and suppression system for autonomous ships |
| title_short | AI-enhanced fire detection and suppression system for autonomous ships |
| title_sort | ai enhanced fire detection and suppression system for autonomous ships |
| topic | Autonomous fire detection and suppression system Artificial intelligence Sensor fusion Stereo vision Ship motion |
| url | http://www.sciencedirect.com/science/article/pii/S2092678224000475 |
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