Development and Optimization of an ESP32-Based Real-Time IoT Platform for Precise Process Control and Monitoring in Aquaculture Systems

This study presents the development and optimization of an Industrial Internet of Things (IoT) platform designed for process monitoring and precise automated feeding in aquaculture systems. As a practical case study for maintaining feeding schedule and dosing consistency, an intelligent automated dosing feeder system for aquariums was engineered. The dual-core ESP32 microcontroller, equipped with integrated wireless communication capabilities, was selected as the central control node. A high-precision DS3231 Real-Time Clock (RTC) module with temperature compensation was integrated to achieve accurate timing control. To improve the dynamic performance of the automated dosing mechanism and achieve precise feed dispensing, a discrete PID control algorithm was implemented within a FreeRTOS multitasking environment at the supervisory process-control level. The PID controller regulates the automated dosing mechanism through the SG-90 servo actuator and does not replace or directly modify the servo motor's internal position-control mechanism. To address integral windup, an anti-windup mechanism was programmatically implemented to clamp cumulative error integration. The PID parameters (, , ) were determined using the Ziegler-Nichols method combined with experimental fine-tuning. Experimental results demonstrated that the optimized system achieved a minimum overshoot of 8%, a settling time of 0.33 s, and a feed portion error within ±0.5 g. Furthermore, the firmware employs task synchronization mechanisms, including message queues, to prevent resource contention during Wi-Fi data transmission and hardware execution. The developed platform supports remote process monitoring through a Wi-Fi-based HTTP API and embedded web interface, while Deep Sleep operation is used to reduce energy consumption between operational cycles. The developed system provides a practical framework for automated precision feeding and process monitoring in aquaculture applications, with potential for further integration of environmental sensors and advanced data-driven control methods.