Ear-stone resonance and artificial intelligence-based parent cobia selective fishing method and system
By measuring the otolith resonance frequency of large yellow croaker, designing tunable acoustic signals, and combining them with deep learning models to optimize parameters, the problems of accidental capture of juvenile fish and ecological damage in traditional large yellow croaker fishing methods have been solved, achieving precise and efficient capture of parent fish.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- ZHEJIANG OCEAN UNIV
- Filing Date
- 2025-04-07
- Publication Date
- 2026-07-14
AI Technical Summary
Traditional large yellow croaker fishing methods lack selectivity, leading to the accidental capture of juvenile fish and ecological damage. Existing acoustic trapping technology is difficult to dynamically adapt to the otolith resonance characteristics of fish of different body lengths and lacks real-time feedback.
By measuring the otolith resonance frequency of large yellow croaker, a body length-resonance frequency mapping model was established, a tunable acoustic signal was designed, and underwater and optical sensors were used to monitor the dynamics of fish schools. The acoustic parameters were optimized using a deep learning model, and selective fishing of parent fish was achieved by combining acoustic and light-induced techniques.
It achieves precise capture of adult large yellow croaker, significantly reduces the accidental capture rate of juvenile fish, improves capture efficiency and survival rate of adult fish, and is adaptable to the environment.
Smart Images
Figure CN120391403B_ABST