Artificial intelligence analysis for feed ratio optimization in precision aquaculture - Galenius, Bryan Timothy (Nanyang Technological University, 2024)
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 summarizing and combining the different behavioral parameters which has been found to be useful in determining hunger into 5 parameters: Weighted Positional Index, Position Variance, Average Speed, Lingering Count, and Average Swim Direction and Turning Angle.