A Forecasting Model for Monitoring Water Quality in Aquaculture and Fisheries IoT Systems

Water quality monitoring is an important task when developing IoT systems, especially for aquaculture and fisheries. By monitoring the real-time indicators (e.g., temperature, salinity, pH, Dissolved Oxygen - DO, and Chemical Oxygen Demand - COD) and getting early warning we can manage the quality of the water, thus collecting both quality and quantity in fish raising. In this work, we propose an IoT system for monitoring water quality in aquaculture and fisheries, especially the model for forecasting the quality indicators. Experimental results on two data sets show that the proposed approach can be applied for the real system.