<![CDATA[. The study purpose was to design and evaluate an IoT-based Automatic Fish Feeder system that integrates sensing, processing, communication, and energy subsystems to improve feeding efficiency in freshwater aquaculture. This research addresses common challenges in manual feeding practices, including inconsistent feeding schedules, inaccurate feed volumes, and lack of real-time monitoring. The system incorporates an ESP32 microcontroller, ultrasonic sensor, servo actuator, and the Blynk platform, supported by a solar-powered energy subsystem, to create a reliable and autonomous feeding mechanism. The objective of the study was to assess the system’s performance through quantitative indicators including response time, sensor accuracy, notification reliability, WiFi stability, feed volume consistency, and energy autonomy. Materials and methods. This study employed a quantitative experimental approach in which the prototype underwent repeated testing under controlled and semi-field conditions. Performance data were collected through direct measurements, digital logs from the Blynk application, and hardware-based monitoring tools. Each subsystem was analyzed based on predefined performance thresholds, and system evaluation was conducted using measurement and structural modeling principles adapted from engineering validation frameworks. Results. The findings indicate that the ESP32 microcontroller produced a consistent response time below two seconds, while the ultrasonic sensor achieved accuracy above ninety-five percent after calibration. Notification reliability exceeded ninety percent, and WiFi stability reached more than ninety-five percent uptime. The solar energy subsystem provided sufficient power for continuous operation, and feed dispensing remained consistent across multiple trials. These outcomes show that the system fulfills its intended functional criteria. Conclusions. The study concludes that the IoT-based feeder operates effectively as an integrated automated system capable of enhancing feeding consistency and reducing manual workload in aquaculture. The prototype is reliable, energy-efficient, and suitable for further development and field-scale implementation.]]>
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