Risk monitoring model of intelligent agriculture Internet of Things based on big data

Abstract

With the development of the times, there is a huge amount of data in every industry. Big data technology is to collect, analyze, process and information from these huge data and apply it to all aspects of our life to improve people's production life. The proposal and development of smart agriculture will play a significant role in the further implementation of the country's rural revitalization strategy. However, the research on risk monitoring in smart agriculture is not yet systematic enough. The purpose of this article is to strengthen the development of smart agriculture under big data, focusing on risk monitoring. To this end, this article studies big data monitoring through data analysis methods and Internet of Things technologies, and discusses the principles of big data and key technology principles of the Internet of Things. Explained, and proposed a modern agricultural technology platform based on the Internet of Things and big data. This platform is established on the basis of precision agriculture and wireless sensor network work, and analyzes the accuracy of various types of light wavelengths for determining wheat rust. The analysis results show that the accuracy of light with multiple wavelengths is not necessarily better than the light with a single wavelength. The accuracy of 600 nm wavelength can reach 100 %, and the accuracy of monitoring with 4 wavelengths together is rather low. However, less consideration is given to the factors in this article, and wheat does not necessarily cause only one disease. Comprehensive analysis is required. With the help of spectral research and aerial photography of drones, the severity of the disease and the outbreak area can be speculated.