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

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Authors: Yihao Liu, Tianfei Cheng, Hanfeng Zheng, Cuihua Wang, Yang Dai, Shufen Zhang, Wei Fan, Zuli Wu, Hui Fang
Cited by: 2
References: 33

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.

Fields of Study & Subjects

Marine Bivalve and Aquaculture Studies Food Supply Chain Traceability Water Quality Monitoring Technologies

Publication details

Journal / source
Fishes
Publisher
MDPI AG
Volume
11
Issue
3
Pages
134–134
Publication date
26 February 2026
Language
EN