Effect of Lettuce on Different Recirculation Intervals of an IoT-Based Hydroponics System Using Deep Flow Technique

In hydroponics, nutrient management is a significant step because maintaining the parameters is essential to the plants. Hydroponics nutrient solution must maintain the pH and EC at adequate levels for optimal plant growth. This paper presents a system for monitoring hydroponics using a wireless sensor node based on the Internet of Things (IoT). Two sensor nodes were utilized in the system: The first node monitors the water quality in the greenhouse, and the second node is in charge of monitoring the pump status. The ESP32 Wi-Fi module and the MQTT communication protocol were utilized to create a monitoring system in this study for lettuce production using Deep Flow Techniques (DFT) to compare the growth and yield with three recirculation intervals of water nutrients. The system monitors the pH level, electrical conductivity, and water temperature, assuring that yields grow in optimal conditions. Also, display the status of the pump whether it is its turn on or off. Data collected by sensors are stored via the internet in cloud-based technologies as the backend. The plant harvested was significantly affected by recirculation intervals of 30 minutes every hour, 12 and 24 hours. However, all compounds analyzed were significantly higher with recirculation interval of 30 minutes in every hour lettuce based on fresh weight.