Abstract
During the entire process of cotton growth and development, diseases and pests occur frequently. Therefore, effective prevention and control of them has always been a difficult problem for agricultural scientists and cotton farmers. This article designed a real-time monitoring and early warning system for cotton pests and diseases. The data processing and analysis module can process and analyze the collected data, and uses technologies such as image recognition and data mining to achieve real-time recognition of cotton diseases and pests. Real-time monitoring of its operation was achieved through the mobile display and management module, enabling users to timely grasp the situation of cotton fields and take corresponding measures. This article compared the monitoring effectiveness and efficiency of traditional manual monitoring methods and agricultural Internet of Things (IoT) based systems in the same farmland. The accuracy of traditional manual monitoring methods was 85%, while agricultural IoT systems showed higher accuracy, reaching 95%. Real-time monitoring and early warning of cotton diseases and pests based on the agricultural Internet of Things is helpful for the prevention and control of flower diseases and pests and cotton field management.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call