<![CDATA[Aquaponic systems require stable environmental control to maintain the balance between fish and plant growth. This study proposes a novel Internet of Things (IoT)-based smart aquaponic system that integrates real-time monitoring, adaptive automatic control, and cloud-based data management within a unified sensor–edge–cloud architecture. The key innovation of this work lies in the seamless integration of the Firebase Realtime Database for low-latency synchronization, an interactive web-based dashboard for real-time visualization, and a hysteresis-based adaptive control mechanism that overcomes the limitations of conventional threshold-based systems, particularly rapid actuator switching (chattering). The system employs an ESP32 as the main processing unit, a DHT11 sensor for temperature and humidity measurement, and a TDS sensor for dissolved nutrient monitoring. Data are transmitted every 10 seconds to the cloud and complemented by event-driven Telegram notifications to enable timely user intervention. Experimental results demonstrate stable system performance, achieving a data transmission success rate of 98.47% over 24 hours. The temperature measurement shows a Mean Absolute Error (MAE) of 0.48°C (≈1.6% relative error), while an average latency of 1.4 seconds indicates responsive real-time synchronization. Furthermore, the implementation of hysteresis-based control effectively reduces actuator instability and enhances system reliability. These findings indicate that the proposed integrated architecture not only improves monitoring accuracy and control stability compared to existing IoT-based aquaponic systems, but also enables practical, remotely accessible, and scalable solutions. The system is particularly suitable for small- to medium-scale aquaponic applications, supporting data-driven decision-making and contributing to sustainable agriculture practices.]]>
