Abstract: In order to build a real-time monitoring system of crop environmental information and realize intelligent management of crop growth, an intelligent agricultural monitoring and management system was constructed. Firstly, based on the Internet of Things technology, the intelligent agricultural monitoring and management system was built with STM32 as the control core from three dimensions of perception layer, transmission layer and application layer. The environmental data such as environmental temperature and humidity, soil temperature and humidity, light intensity and air quality, etc, were collected through sensors, and transmitted to the server using a wireless module to achieve monitoring and remote control of environmental factors. Secondly, the image processing algorithm and SVM model based on OpenCV database were used to classify and recognize crop disease images. Finally, the upper computer UI interface was designed based on the QT platform. Through experimental tests, the system was accurate and reliable in information transmission and equipment control. The average accuracy rate of the system for disease image classification was 96.3%, and the accuracy rate of pomegranate brown spot recognition was the highest, reaching 97.4%.

Key words: Internet of Things, intelligent agriculture, monitoring and management system, image recognition, SVM