Design of Smart Cane Field Management Monitoring System based on Kalman Filter Algorithm

In this paper, for the traditional sugarcane planting inaccurate fertiliser application, pest and disease control difficulties, relying on artificial experience to produce planting and other issues, from plant irrigation, information transfer and data processing three aspects, in-depth research, using Kalman filter algorithm to monitor the data filtering and denoising process, improve the measurement accuracy, reduce the error, the use of the Internet of Things (IoT) sensor technology and wireless communication technology, to achieve field environment real-time monitoring, efficient use of water resources and early warning of pests and diseases. The experiments were carried out by establishing a simulation model, and the experimental results showed that this technology is highly feasible and provides a scientific basis for further improving the efficiency and yield of sugarcane field management.