This paper describes the development of a platform for monitoring water quality in fish farming using IoT and cloud computing concepts. The tool collects real-time data through sensors on the main physical and chemical parameters of the water, such as temperature, pH, turbidity, and dissolved oxygen. These data are then processed and made available in the cloud for the fish farmer to access. Additionally, to validate the context of the platform’s data, a machine learning model was developed using Orange Data Mining to predict the percentage of feed to be given to the fish based on the collected data. The results achieved showed that the
platform provides an efficient and effective means for fish farmers to monitor water quality and predict feeding in their fish farming operations.