ESP32 IoT Auger‑Based Automatic Feeder for Fish Pellets - Aqid Mukhtar; Ahmad Munir; Abdul Azis (Salaga Journal, 2025)
Manual fish feeding in aquaponics often leads to inconsistent schedules and imprecise dosing, degrading water quality and system performance. This study designs and builds an ESP32‑based IoT automatic fish feeder using an auger dispensing mechanism controlled via the Blynk platform. The objectives are to develop a reliable feeder, calibrate dosing for different pellet sizes (1, 2, and 3 mm), and evaluate scheduling accuracy and dosing precision. The prototype consists of a 3 kg acrylic hopper (45° angle of repose), a cast‑iron auger, and an ESP32 control module with a servo and DC motor driven by an L298N driver. Calibration established linear models between servo rotation time and feed dose, and between motor PWM and throwing distance. Performance tests were conducted over three days with twice‑daily feeding. Results show strong linearity in calibration (dose–time R² > 0.997; PWM–distance R² > 0.92), perfect schedule adherence (zero delay at 08:00 and 15:00), and high dosing accuracy across pellet sizes, with average errors of 2.37% (1 mm), 3.04% (2 mm), and 2.94% (3 mm) (overall mean 2.78%). In conclusion, the system integrates mechanical reliability, electronic control, and IoT accessibility to deliver precise, scheduled, and remotely controllable feed management for aquaponics. The approach is practical and low‑cost, and it contributes to smart aquaculture by enhancing operational efficiency and reducing labor dependency.