Artificial intelligence analysis for feed ratio optimization in precision aquaculture

Artificial intelligence analysis for feed ratio optimization in precision aquaculture

Aquaculture products’ increasing demand emphasizes the importance of FCR (Feed Conversion Ratio) optimization. While efforts to improve FCR of specific species exist, a universal method is lacking. Therefore, we present a hunger detection method generalized for different aquaculture species by...

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Bibliographic Details
Main Author: Galenius, Bryan Timothy
Other Authors: Ng Yin Kwee
Format: Final Year Project (FYP)
Language:English
Published: Nanyang Technological University 2024
Subjects:
Computer and Information Science
Engineering
Aquaculture
Computer vision
Satiety
Machine learning
Hunger detection
Online Access:https://hdl.handle.net/10356/176594

Internet

https://hdl.handle.net/10356/176594

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