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.