Smart Aquaculture: Machine Learning-Based Water Quality Prediction in Kadammakudy's Pokkali Fields, Ernakulam

Climate change and pollution pose profound threats to aquatic ecosystems, imperiling the long-term viability of aquaculture. To mitigate these impacts, we developed a novel Real-Time Prediction Model integrating Edge Computing and Explainable Artificial Intelligence (XAI) specifically designed for farmer accessibility in Kadamakkudy's Pokkalifields, Ernakulam. Leveraging an ensemble of predictive algorithms, our model accurately forecasts critical water quality parameters. Despite limited daily measurements, timely interventions are enabled, safeguarding both ecological balance and agricultural profitability. By ensuring interpretability and openness, XAI enables farmers to make data-driven, well-informed decisions that balance environmental and economic sustainability.