Development of Fuzzy Logic Automatic Fish Feeding System and Iot-based Water Quality Control

Abstract

Rapidly developing technological advances make it easier for fish farmers to manage fish farming systems in an intelligent, structured, and modern way. This study discusses how IoT and fuzzy logic can be used to improve fish farming in an intelligent and modern way, which includes discussing important issues in managing water quality and optimizing fish feeding. The purpose of this study is to develop an IoT-based water quality control system and an automatic fish feeder based on a fuzzy logic controller. The method used in this study is the research and development (R n D) method. The input parameters in this study are temperature, pH, and water clarity, while the outputs in this study are: aerator working duration, heater working duration, cooler working duration, motor working duration, and the amount of fish feed. The results of the study showed an average error percentage of <5% so that the sensor can work accurately in determining water quality and determining the amount of feed; 2) the water quality control system can work well, where the heater, cooler, and aerator can work according to the quality of the pond; 3) the automatic fish feeding system has an average percentage of <5% so that it can work well and precisely in determining the duration of the motor and the amount of fish feed.