Intelligent Fusion Technology of Crop Growth Monitoring Data Under Wireless Sensor Networks

Abstract

Using adaptive weighted data fusion technology, the relative error of crop growth monitoring data is relatively large, accuracy is not high, and its fusion is not effective. In view of the above problems, the intelligent fusion technology of crop growth monitoring data under wireless sensor network is proposed. The technology consists of three parts: Using LEACH (Low Energy Adaptive Clustering Hierarchy) protocol to realize rapid processing and transmission of monitoring data. Accurate fusion of monitoring data through BP (Back Propagation) neural network; the two models are combined to construct the data fusion algorithm BPDFA (Back-Propagation Data Fusion Algorithm) model, so as to achieve intelligent fusion of crop growth monitoring data. By using the unique information processing characteristics of BP neural network, multi-information processing and transmission at the same time, the efficiency of processing is improved, and the fusion of crop growth information is realized. The results show that the intelligent fusion technology and adaptive weighted data fusion technology proposed in this study, the relative error is reduced by 3.72 °C, the accuracy is higher, and the fusion effect is better.