现代农业领域中，通过使用各种传感器和不同的算法实现灌溉系统的自动化，使灌溉过程完全自主。设计了基
于物联网的智能灌溉系统，利用传感器获取温度、湿度等数据，通过节点MCU处理并上传云端服务器进行储存，使用应用程
序Blynk来实时监测数据，应用机器学习算法对实时传感器数据进行分类，通过决策树算法在脚本中实现。
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.
