<![CDATA[Manual plant irrigation often leads to inefficient water usage and delayed responses to changing environmental conditions. This study aims to develop and implement an Internet of Things (IoT)-based monitoring and automatic irrigation system using ESP32 and ESP32-CAM. The proposed system continuously monitors air temperature, humidity, soil moisture, and light intensity while simultaneously capturing plant images for remote observation through a web-based interface. A zero-order Sugeno Fuzzy Logic algorithm is employed to determine irrigation duration based on soil moisture and light intensity inputs, enabling adaptive watering decisions according to environmental conditions. Sensor data and captured images are transmitted to a remote server and displayed through a monitoring website for real-time access. Outdoor testing demonstrated that the system was able to continuously monitor environmental parameters, perform adaptive irrigation based on fuzzy inference results, successfully transmit sensor data to the database, and synchronize captured images with the web platform. The experimental results indicate that the proposed system can provide reliable monitoring and automated irrigation functions, supporting the implementation of IoT-based smart agriculture applications.]]>
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