Implementation of Internet of Things-Based Autofeeder to Maintain Koi Pond Water Quality
Helmy Helmy (1*), Suko Tyas Pernanda (2), Septiantar Tebe Nursaputro (3), Mona Inayah Pratiwi (4), Brian Rahmaditya (5), Clara Silvia Anggreini (6) (1) Politeknik Negeri Semarang - Indonesia
(2) Politeknik Negeri Semarang - Indonesia
(3) Politeknik Negeri Semarang - Indonesia
(4) Politeknik Negeri Semarang - Indonesia
(5) Politeknik Negeri Semarang - Indonesia
(6) Politeknik Negeri Semarang - Indonesia
(*) Corresponding Author
Received: December 12, 2024; Revised: August 04, 2025
Accepted: August 22, 2025; Published: December 31, 2025
Abstract
Koi fish farming requires careful monitoring of water temperature and pH to prevent adverse impacts on the fish. This study presents a prototype IoT-based autofeeder that integrates real-time water quality monitoring and automatic feeding, controllable via both an Android application and local device buttons. The system allows users to configure feeding schedules, feed throw levels, and durations, as well as set pH thresholds. When the pH exceeds the safe range, the system automatically stops feeding and sends notifications, enabling the user to inspect and maintain pond water quality. The findings demonstrate that the dispensing level significantly influences the feed-throwing distance; higher dispensing levels result in longer distances. Small-sized feed (S) consistently produced the highest output, followed by medium-sized (M) and large-sized (L). Increasing the feeding duration enhanced the weight of the released feed. Additionally, the average delay in sensor data transmission to the database was recorded at 5.48 seconds. The data loss rate during the testing period was 1.72%, which is considered acceptable and does not adversely affect system operations. The data transmission system demonstrated good and stable performance with relatively low data loss.
http://dx.doi.org/10.55981/jet.717 Keywords
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