In modern agriculture, irrigation systems are automated by using various sensors and different algorithms to make the irrigation process fully autonomous. In this paper, an intelligent IoT-based irrigation system is designed, using sensors to obtain data

such as temperature and humidity, which is processed by a node MCU and uploaded to a cloud server for storage. The application

Blynk is used to monitor the data in real time, and a machine learning algorithm is used to classify the real-time sensor data, which is implemented in a script using a decision tree algorithm.