Design and Simulation of an IoT-Based Adaptive Control System for Urban Hydroponic Farming

Abstract

Efficient water circulation is an essential requirement in urban hydroponic farming, yet many systems still depend on fixed timer control that cannot adjust to changing environmental conditions. This study develops an Internet of Things based adaptive pump control system that responds to real-time temperature and humidity data collected using DHT22 and DS18B20 sensors. An ESP32 microcontroller manages the sensing and control process, while MQTT and Blynk Cloud enable continuous monitoring and data exchange. The system is evaluated through a six hour hydroponic simulation on the Wokwi platform under three environmental scenarios: Normal, Heatwave, and Humid. Two control strategies are compared, the fixed interval mode (K1) and an adaptive mode (K2) based on threshold rules. The results show that the adaptive mode improves water efficiency by reducing pump operation by 23.4 percent on average while maintaining more stable temperature and humidity conditions. These findings indicate that lightweight IoT solutions can support responsive and efficient operation in urban hydroponic systems, offering a practical basis for further development of intelligent control in urban farming.