In hydroponic farming, optimal pH value is important to regulate nutrient availability for efficient plant growth. This study aims to design an autonomous pH monitoring and control system for maintaining an optimal pH range. The prototype was developed for data acquisition, data processing and data visualization to ensure that the measured nutritional solution parameters are within the specified range: temperature (18–35°C), pH (5.5–8.0), and dissolved oxygen level (>2 ppm). Data collected at sampling rate of 10 seconds utilising temperature sensor, pH sensor, and dissolved oxygen sensor were processed using a microcontroller on a Node-RED interface in a Raspberry Pi. The processed data were stored in InfluxDB before being displayed in Grafana. If the value exceeded the threshold, a Telegram alert was delivered to the end-user. The pH data were used to build a framework to control the pH levels within range. Two peristaltic pumps (DFRobot, DFR0523) were utilized to pump potassium hydroxide or phosphoric acid solution if the pH was out of range. The developed prototype was able to automatically control the pH within the optimum range in the nutrient solution, which will positively impact the nutrient adsorption and subsequent plant growth in a hydroponics system.

Maintaining Dissolved Oxygen (DO) levels in the hydroponic plant nutrient solutions can be done using nanobubble technology. Manual monitoring can be time-consuming and measurement results are less accurate. Therefore, a monitoring system is needed to monitor air temperature, air humidity, water temperature, water pH, nutrient concentrations, and DO levels. Several stages in this research are preparation, design, sensor calibration, and monitoring system implementation. Air temperature and humidity conditions can be measured with the DHT22 sensor, water temperature can be measured with the DS18B20 sensor, water pH can be measured with the Analog pH Meter Pro, nutrient density can be measured with the Analog TDS sensor, and DO levels can be measured with the Dissolved Oxygen Sensor. Based on the measurement results monitored by the monitoring system, the parameters that affect the ignition of the nanobubble generator are DO values and water temperature. The system can also visualize sensor data on monitors and online, and can store sensor data locally and IoT so that this system has the potential to monitor hydroponics, especially nanobubble-based hydroponics. Keywords:   Sensor, Dissolved Oxygen, Arduino Uno, ESP32-E, NodeMCU ESP8266