Authors

Abstract

To realize the real-time remote monitoring of the jujube orchard environment and the prediction of irrigation amount, an intelligent irrigation system was designed in this study by using sensors, Internet of Things (IoT), and backpropagation (BP) neural network. In this system, the jujube tree is taken as the test object, the meteorological data are used as the model feature input vector, the BP neural network prediction model is used to predict the water demand of the crop, and data visualization monitoring and remote control of the irrigation switch are realized using the IoT platform and mobile terminal platform.

Abstract in Chinese

为实现枣树园环境的实时远程监测和灌溉量的预测，设计了基于传感器技术、物联网技术及人工智能技术相结合的智能灌溉系统。该系统以枣树为试验对象，以气象数据作为模型特征输入向量，运用BP神经网络预测模型预测作物当前需水量，并通过物联网平台与移动端平台实现数据可视化监测和灌水开关远程控制。