Embedded Design and Implementation of a Wireless Multimedia Platform for Digital Estimation of Agricultural Output

The estimation of agricultural output is an important issue in the digital development of modern agriculture. Using embedded technology, this paper designs a multimedia platform for digital estimation of agricultural output. The terminal design of the multimedia platform selects the Intel Xscale series PXA255 processor as the core processor, uses multiple sensors to collect agricultural output-related environmental parameters and selects the digital media processing chip TMS320DM642 for multimedia processing. The software used selects the grey relational Support Vector Machine (SVM) algorithm to estimate agricultural output. First, the collected agricultural sown area, labor force, mechanical power, irrigated area, agricultural production environment and other parameters are collected as input to grey relational SVM. Second, the estimated results are outputted. Finally, the results of agricultural output estimation are digitally displayed by a display interface on the embedded multimedia terminal. The experimental results show that the prediction error is less than 1%, and the prediction accuracy is higher than 99%, which validates that the method can accurately predict agricultural output with an abundance of applications.

Automated summary

This paper presents the design of a multimedia platform for digitally estimating agricultural output. By utilizing embedded technology, the platform collects environmental parameters related to agricultural output and utilizes the grey relational Support Vector Machine algorithm for prediction. Experimental results demonstrate that this method accurately predicts agricultural output with high precision and has abundant applications.