Smart Aquaponics: Water Quality Monitoring and Cloud Based Alert

This study presents a unique method for integrating machine learning and cloud computing to monitor water quality indicators in aquaponics systems. The integrated farming method known as aquaponics, which combines hydroponics with aquaculture, depends on maintaining environmental conditions for the best possible development of plants and fish. The system quickly identifies changes from ideal circumstances by monitoring temperature, turbidity, dissolved oxygen, pH, ammonia, and nitrate levels continually. Alerts are created and sent to farmers when parameters deviate from permissible bounds, allowing for prompt action to reduce possible problems. Using machine learning methods, namely LightGBM (LGBM), our suggested alert system achieves an amazing accuracy of 99.98%. By utilizing an integrated approach, aquaponics farming operations are made more efficient and productive, guaranteeing sustainable output and protecting the health of fish and plants alike.