Abstract: As an important link in the fishery industry chain, the efficiency and quality of live fish transportation are crucial. However, traditional transportation methods suffer from high labor intensity, low efficiency, and heavy reliance on human expertise. The development of artificial intelligence (AI) provides innovative technological solutions to address these challenges. Studies indicate that AI-driven technologies can significantly enhance transportation efficiency, reduce costs, and mitigate fish stress responses, thereby improving transportation quality. Nevertheless, AI applications in live fish transportation still face various challenges, such as data processing in complex environments, sensor stability and cost issues, and real-time algorithm requirements. This paper reviews the potential applications of AI in live fish transportation, including monitoring and classification of fish stress responses, real-time water quality regulation based on machine vision and intelligent sensors, route optimization algorithms, and application scenarios of autonomous driving technology. This paper aims to provide theoretical support and practical references for the application and promotion of AI technology in live fish transportation.

Key words: live fish transportation, artificial intelligence, sensors, autonomous driving, intelligent algorithm