An Integrated Safety Monitoring and Pre-Warning System for Fishing Vessels

Fishing vessels are essential for the activities of catching, moving, and storing fish. However, fishing vessel accidents claim thousands of deaths every year. This study presents a novel integrated safety monitoring and early warning system designed for fishing vessels, offering significant advancements in maritime safety through real-time alerts based on vessel attitude motion and environmental conditions. The innovation of the system lies in its dual-subsystem architecture: a sensing terminal equipped with a nine-axis sensor, temperature and humidity sensors, a GPS module, and a surveillance camera collects critical data, while a decision support subsystem processes this information via a fuzzy logic-based algorithm to generate a “danger score”. This score quantifies the vessel’s safety status, enabling the system to trigger alerts through SMS and web notifications when predefined thresholds are exceeded. Field trials in the Zhoushan Sea area confirmed the system’s effectiveness in accurately predicting safety hazards and providing timely alerts. The results highlight its potential to enhance operational safety and contribute to the digitization of fisheries management by offering reliable real-time data on vessel conditions. The system’s modular and cost-efficient design ensures it is scalable and adaptable for widespread use across the fishing industry. Our study addresses the limitations of existing technologies by providing a balanced solution that combines comprehensive sensing capabilities with real-time responsiveness and cost-effectiveness, offering a practical and innovative approach to improve fishing vessel safety.

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Publication Details

Journal
Journal of Marine Science and Engineering
Published
2025-05-26
DOI
https://doi.org/10.3390/jmse13061049
Primary Topic
Maritime Navigation and Safety
Type
article
Field-Weighted Citation Impact
0.00

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article

An Integrated Safety Monitoring and Pre-Warning System for Fishing Vessels

Li Qin, Jinglong Lin, Jianjun Ding, Kun Yang et al.
Journal of Marine Science and Engineering
Maritime Navigation and Safety
article

An Integrated Safety Monitoring and Pre-Warning System for Fishing Vessels

Li Qin, Jinglong Lin, Jianjun Ding, Kun Yang, Bing Zheng
article en

Abstract

Fishing vessels are essential for the activities of catching, moving, and storing fish. However, fishing vessel accidents claim thousands of deaths every year. This study presents a novel integrated safety monitoring and early warning system designed for fishing vessels, offering significant advancements in maritime safety through real-time alerts based on vessel attitude motion and environmental conditions. The innovation of the system lies in its dual-subsystem architecture: a sensing terminal equipped with a nine-axis sensor, temperature and humidity sensors, a GPS module, and a surveillance camera collects critical data, while a decision support subsystem processes this information via a fuzzy logic-based algorithm to generate a “danger score”. This score quantifies the vessel’s safety status, enabling the system to trigger alerts through SMS and web notifications when predefined thresholds are exceeded. Field trials in the Zhoushan Sea area confirmed the system’s effectiveness in accurately predicting safety hazards and providing timely alerts. The results highlight its potential to enhance operational safety and contribute to the digitization of fisheries management by offering reliable real-time data on vessel conditions. The system’s modular and cost-efficient design ensures it is scalable and adaptable for widespread use across the fishing industry. Our study addresses the limitations of existing technologies by providing a balanced solution that combines comprehensive sensing capabilities with real-time responsiveness and cost-effectiveness, offering a practical and innovative approach to improve fishing vessel safety.

Journal of Marine Science and EngineeringVol. 13(6)
Ministry of Natural Resources (CN), Zhejiang Ocean University (CN), Guangzhou Marine Geological Survey (CN)
National Natural Science Foundation of China, Natural Science Foundation of Ningbo
Openalex Percentile: Top 86%
Maritime Navigation and Safety
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