Abstract

In recent years, with the rapid economic development, the development of emerging technologies is changing with each passing day, and the process of agricultural informatization has been further promoted. At present, the intelligent application represented by the intelligent agricultural data collection and analysis system has been widely used, and the degree of agricultural informatization has been improved. The purpose of this paper is to study the design and implementation of the smart agricultural data collection and analysis system based on the Internet of Things technology. Research and analyze the business requirements in smart agriculture, and choose the MongoDB database with the built-in GridFS file system as the best storage solution. Then, combined with the characteristics of agricultural data and the document characteristics of MongoDB, a MongoDB-based agricultural data storage model is constructed. An agricultural big data analysis algorithm based on clustering is proposed. Using this method, the massive agricultural production data generated by the agricultural Internet of Things can be analyzed, and the data of the remote monitoring terminal can be clearly obtained in the remote monitoring module. The system meets the requirements.

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