Automated Fish Feeding System and Real-Time Water Quality Monitoring Based on Internet of Things for Milkfish Aquaculture

Abstract

Milkfish (Chanos chanos) aquaculture in Indonesia still relies heavily on manual feeding and periodic water quality monitoring, which increases the risk of operational inefficiency and human error. This study designs and implements an integrated Internet of Things (IoT)-based prototype to automate feeding and monitor real-time water quality parameters, including temperature, turbidity, and water level, in milkfish ponds. The system uses an ESP32 microcontroller connected to a DS18B20 temperature sensor, HC-SR04 ultrasonic sensors for water level and feed volume detection, an FC-51 infrared sensor for feed presence detection, and a turbidity sensor. Data transmission is carried out using the MQTT protocol over WiFi and displayed through web and smartphone-based interfaces. The novelty of this study lies in the integration of automated feeding with multi-parameter real-time water quality monitoring specifically designed for milkfish pond conditions in Indonesia, incorporating MQTT-based communication architecture and a dual-platform monitoring interface. Prototype validation showed that scheduled feeding was executed successfully across three daily feeding sessions. Sensor testing produced small measurement deviations, with a temperature deviation of 0.1°C, a water level deviation of 0.2 cm, and a turbidity deviation of 0.2 NTU. The MQTT communication latency ranged from 120 to 180 ms under normal conditions. These results confirm that the proposed system effectively supports automated feeding, real-time pond monitoring, and remote management with low-cost IoT infrastructure.