This study aims to develop and implement an automated greenhouse system based on the Internet of Things (IoT) to monitor and analyze environmental conditions, including temperature, humidity, and light intensity. The system utilizes an ESP32 microcontroller integrated with a DHT22 sensor, soil moisture sensor, and LDR light sensor. Sensor data is transmitted in real time to the Blynk application, enabling users to monitor and control the system remotely via smartphone. The system uses a rule-based approach, such as activating a fan when the temperature exceeds 32°C, activating a water pump when soil moisture is below 30%, and turning on lights when light intensity is low. The experiment was conducted using a laboratory-scale prototype with kangkung plants. The system demonstrated its ability to provide timely and accurate environmental updates, enhancing greenhouse management efficiency. This system shows potential to support optimal plant growth while conserving energy.
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