<![CDATA[Efficient irrigation management and nutrient utilization are essential factors in improving pak choy productivity. This study proposes an Internet of Things (IoT)-based automated irrigation system that integrates an ESP32 microcontroller, soil moisture sensors, rain sensors, Telegram Bot, and n8n workflow automation. The system applies growth-stage-based irrigation scheduling and utilizes catfish pond wastewater as an alternative nutrient source. Irrigation volumes were dynamically adjusted according to plant growth stages, consisting of 0.65 L (days 1–14), 0.63 L (days 15–21), and 0.37 L (days 22–35). System performance was evaluated through communication testing, confusion matrix analysis, and plant growth observations. Experimental results showed average end-to-end delays of 6.0 s for Telegram communication and 11.3 s for n8n integration, with an average command latency of 2.779 s. The irrigation decision mechanism achieved 90% accuracy, 88.9% precision, and 91% recall. Furthermore, pak choy irrigated with catfish pond wastewater demonstrated superior growth performance, reaching 16 cm plant height, 20 leaves, and 81 g harvest weight, compared with 14 cm, 16 leaves, and 67 g under conventional irrigation. These findings demonstrate that the proposed system provides reliable irrigation automation while supporting sustainable agriculture through the reutilization of aquaculture wastewater.]]>
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