Prediction Model based on Bagging and Boosting Ensemble Technique for Decision Support System of Autonomous Smart IIoT Smart Aquaponic System

Abstract The aqua-agriculture food sector, challenged by climate change, exploited biodiversity, insecurity, water crisis, and global pandemic, urgently needs the sustainability transition more sustainable practices. Sustainability transitions aim to transform current patterns of production consumption into ones while enhancing ecological economic situation. This agenda is much possible with integration IIoT AI/ML aqua agriculture. In this study, researchers integrated a Prediction Model based on Bagging Boosting Ensemble Technique in Decision Support System an Autonomous Smart Aquaponic that autonomously monitored, controlled, managed aquaponic systems.