Internet of Things: Water Quality Classifying Based on Estimation Dissolved Oxygen Solubility and Estimation Unionized Ammonia for Small-scales Freshwater Aquaculture - Shandikri, Rheza; Erfianto, Bayu (Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, 2021)
In aquaculture, poor water quality can affect fish growth and mortality. Water quality parameters such as ammonia, temperature, pH, and dissolved oxygen must be controlled and monitored. There are available measuring devices for dissolved oxygen and ammonia levels, but measurements cost is not suitable for small-scale aquaculture and are manually process. Our experimental study proposes the Emerson formula to find the estimated value of unionized ammonia and the Benson-Krause formula to find the estimated dissolved oxygen solubility value without using an ammonia sensor or dissolved oxygen sensor. Internet of things can be applied to aquaculture to monitor and collect water parameter data without human intervention. The values ​​of both estimates are validated using the Seneye Sensor. RMSE and MAE are used to calculate the performance evaluation between the Seneye value and the estimated value. Fuzzy logic clasify water quality derived from estimates of ionized ammonia and estimates of dissolved oxygen as input.