Abstract: To investigate the potential of edge computing technology in intelligent fisheries equipment, this study addresses limitations of traditional cloud computing regarding real-time responsiveness and efficiency by proposing an optimized solution through relocating computational resources closer to the network edge. The research systematically reviews the development history of edge computing technology and emphasizes the critical technologies in intelligent fisheries equipment, such as computational offloading and data storage and management. By analyzing typical fishery application scenarios, the role of edge computing in improving real-time data processing and system responsiveness is highlighted. Results indicate that edge computing significantly alleviates network bandwidth constraints and transmission latency issues by decentralizing computational resources, thereby enhancing the real-time performance of intelligent fisheries equipment. Nevertheless, challenges such as limited computing capabilities of edge devices and insufficient coordination among heterogeneous equipment continue to hinder broader adoption. With deeper integration of edge computing with artificial intelligence, big data, and the Internet of Things (IoT), edge computing promises further improvements in remote data transmission, IoT integration, intelligent decision-making, and sustainable development in intelligent fisheries. This advancement is expected to drive the fisheries industry toward greater intelligence, efficiency, and ecological sustainability.

Key words: edge computing, edge intelligence, computation offloading, intelligent detection, intelligent equipment; 

摘要： 为研究边缘计算技术在渔业智能化装备中的应用潜力，针对传统云端处理在实时性和高效性方面的局限，通过将计算资源下沉至网络边缘，提出优化解决方案。本研究系统梳理了边缘计算技术的发展历程，并重点分析了在渔业智能化装备中的关键技术，如计算卸载、数据存储与管理，结合渔业典型应用场景分析边缘计算在提升实时数据处理与系统响应速度方面的作用。结果显示，边缘计算通过将计算资源下沉至网络边缘，显著缓解了网络带宽与传输延迟的瓶颈，同时有效提升了渔业智能化装备的实时性。然而，边缘设备算力有限及异构设备之间协调性不足等问题，仍在一定程度上阻碍了其应用与推广。随着边缘计算与人工智能、大数据及物联网技术的深度融合，边缘计算有望为渔业智能化在远程数据传输能力优化、物联网深度融合等方面，带来更高的智能决策能力和可持续发展潜力，推动渔业行业向更智能、高效和生态友好的方向发展。

关键词: 边缘计算, 边缘智能, 计算卸载, 智能检测, 智能化装备