Abstract

This article first analyzes big data technology. Then, the agricultural Internet of Things system was established, and the acquisition of agricultural data was achieved through the establishment of sensor modules, image acquisition modules, and meteorological acquisition modules. The data are transmitted to the server through GPRS communication technology and 3G network card to realize data transmission. The Web Service technology is used to connect the Internet of Things with the neural network model to achieve data interoperability. By comparing the prediction results and actual data of the model, it is found that the prediction error of the model designed in this article is less than 1%, and the high-precision prediction of agricultural data is realized, which provides an effective guidance for the improvement of agricultural product quality and yield.

Highlights

  • People’s demand for food is getting higher and higher. the control of agricultural products has become more and more important

  • As the economy develops, people’s demand for food is getting higher and higher

  • This article will use neural network model to which agricultural production, and the agricultural data are processed in time and accurately through the design of the sensor

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Summary

Introduction

People’s demand for food is getting higher and higher. the control of agricultural products has become more and more important. This article will use neural network model to which agricultural production, and the agricultural data are processed in time and accurately through the design of the sensor.

Results
Conclusion
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