Preliminary Exploration of an Informatized Management Model for Deep-Sea Aquaculture: From Land-Based Farming to Offshore Marine Ranches

Offshore and deep-sea aquaculture is increasingly recognized as a key pathway for expanding marine food production as nearshore resources decline and global demand for high-quality aquatic products grows. However, open-ocean farming operates under highly dynamic environmental conditions and long production cycles, which impose significant challenges on conventional experience-based management. This review synthesizes recent research on informatized management in offshore and deep-sea aquaculture and proposes a structured management framework based on five functional layers: perception, transmission, platform, decision, and execution. By systematically analyzing environmental constraints, technical bottlenecks, and management requirements, this framework integrates key technologies including the Internet of Things, unmanned surface and underwater vehicles, big data analytics, and artificial intelligence. The review further examines representative application scenarios, including environmental monitoring and early warning, intelligent feeding and nutrition management, disease prevention and control, and remote monitoring and management. Through cross-study comparison, this work highlights current limitations in system integration and long-term validation, while clarifying the technological pathways required for scalable and reliable offshore deployment. Overall, this review provides a conceptual foundation and technical reference for improving operational safety, production efficiency, and environmental sustainability in offshore and deep-sea aquaculture.

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Publication Details

Journal
Fishes
Published
2026-02-26
DOI
https://doi.org/10.3390/fishes11030134
Primary Topic
Marine Bivalve and Aquaculture Studies
Type
article
Field-Weighted Citation Impact
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article

Preliminary Exploration of an Informatized Management Model for Deep-Sea Aquaculture: From Land-Based Farming to Offshore Marine Ranches

Cuihua Wang, Shufen Zhang, Tianfei Cheng, Hanfeng Zheng et al.
Fishes
Marine Bivalve and Aquaculture Studies
article

Preliminary Exploration of an Informatized Management Model for Deep-Sea Aquaculture: From Land-Based Farming to Offshore Marine Ranches

Cuihua Wang, Shufen Zhang, Tianfei Cheng, Hanfeng Zheng, Wei Fan, Hui Fang, Yihao Liu, Yang Dai, Zuli Wu
article en

Abstract

Offshore and deep-sea aquaculture is increasingly recognized as a key pathway for expanding marine food production as nearshore resources decline and global demand for high-quality aquatic products grows. However, open-ocean farming operates under highly dynamic environmental conditions and long production cycles, which impose significant challenges on conventional experience-based management. This review synthesizes recent research on informatized management in offshore and deep-sea aquaculture and proposes a structured management framework based on five functional layers: perception, transmission, platform, decision, and execution. By systematically analyzing environmental constraints, technical bottlenecks, and management requirements, this framework integrates key technologies including the Internet of Things, unmanned surface and underwater vehicles, big data analytics, and artificial intelligence. The review further examines representative application scenarios, including environmental monitoring and early warning, intelligent feeding and nutrition management, disease prevention and control, and remote monitoring and management. Through cross-study comparison, this work highlights current limitations in system integration and long-term validation, while clarifying the technological pathways required for scalable and reliable offshore deployment. Overall, this review provides a conceptual foundation and technical reference for improving operational safety, production efficiency, and environmental sustainability in offshore and deep-sea aquaculture.

FishesVol. 11(3)
Dalian Ocean University (CN), Ministry of Agriculture and Rural Affairs (CN), Chinese Academy of Fishery Sciences (CN)
Responsible consumption and production
Openalex Percentile: Top 51%
Marine Bivalve and Aquaculture Studies
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